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{"poster":"Daymon","date":"2019-06-15T00:47:52.343+0000","title":"iron-silver looking for ranked friends girls with soc media vouch only add me in game","subforum":"Team Recruitment","up_votes":1,"down_votes":0,"body":"then when i get round to it ill add u and u link me ur soc media validation and we will go from there, dont add me if u dont want to share fb info u filthy cave dweller","replies":[]} |
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{"poster":"LiqsCris","date":"2015-05-01T11:43:03.887+0000","title":"ADC LF Team/Duo","subforum":"Clans & Teams","up_votes":1,"down_votes":1,"body":"wie in dem Topic schon geschrieben, suche ich ein Team als AD-Carry oder einen duo Partner. \r\n\r\nZu mir:\r\n\r\n-Christian\r\n-22 Jahre alt\r\n-Spiele lol seid S2\r\n-Elo: Plat III\r\n-Teamrankederfahrung: G3\r\n-Mainrolle: main ADC seid Season 4\r\n-main champs: graves, cait, sivir, jinx, corki, lucian\r\n- Mitglied des Clan Liquid Souls\r\n\r\nWas ich erwarte:\r\n\r\n-SoloQ Elo S5 mindestens Plat\r\n-kein Rage/Flame\r\n-Pünktlichkeit,Zuverlässigkeit,Engagement, Zeit zum trainieren\r\n-Auswertung der Spiele\r\n-Bei Interesse kann das Team auch unter dem Clan spielen\r\n-Duo Partner muss nicht unbedingt Main Supp sein.\r\n\r\nMeine Ziele:\r\n-bei Interesse des Teams, besteht die Möglichkeit im Clan Liquid Souls zu spielen.\r\n-Teilnahme an Turnieren,\r\n-mind Gold/Plat als Team\r\n\r\nSo das wars von mir eigentlich auch schon. Wenn ihr zufällig einen AD-Carry sucht, dann addet mich doch einfach und wir besprechen Weiteres.\r\n\r\nLiebe Grüße\r\nliQs Score","replies":[{"poster":"LiqsCris","date":"2015-05-02T09:29:37.127+0000","up_votes":1,"down_votes":0,"body":"push","replies":[]},{"poster":"LiqsCris","date":"2015-05-01T13:01:41.428+0000","up_votes":1,"down_votes":0,"body":"push","replies":[]},{"poster":"Duck Dynasty","date":"2015-05-01T12:37:22.805+0000","up_votes":1,"down_votes":0,"body":"hai ich interessiere mich für den clan und soloQ . spiele momentan Allrounder aber würde mich gerne auf Main supp konzentrieren.ich bin 26 Jahre und die reife ist auch da.Ich besitze Ts und skype.Wenn du Interesse hast adde mich. LG","replies":[]},{"poster":"KDAlex","date":"2015-05-01T12:32:46.861+0000","up_votes":1,"down_votes":0,"body":"Leider nur Gold 3 atm :D","replies":[]},{"poster":"LiqsCris","date":"2015-05-01T12:24:31.851+0000","up_votes":1,"down_votes":0,"body":"push","replies":[]}]} |
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{"poster":"Dragoras","date":"2015-03-08T09:18:58.299+0000","title":"Platin sucht Team","subforum":"Clans & Teams","up_votes":1,"down_votes":1,"body":"Hey suche ein ranked team \n\nzu mir bin 18 hab headset und ts\nmain lane ist sup und top und danach mid\nbin platin 5 mit 60 pkt momentan\n\nich war jetzt lange in einem team aber dass ist auseinander gebrochen wegen diversen gründen deswegen suche ich ein team das am besten schon eingespielt ist und einfach einen 5 braucht oder jenachdem einen 5 und 4 braucht\n\nmfg Dragoras","replies":[]} |
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{"poster":"Orvvadasz1","date":"2016-11-08T11:26:31.141+0000","title":"Az új fejléc (hiba)","subforum":"Segítség és támogatás","up_votes":2,"down_votes":1,"body":"Az új fejlécen ha telefonról nyitom meg a hiba bejelentést (felkiáltójel) akkor nem lehet elolvasni a szöveget mert túl nagy az ablak és kilóg a képernyőről. (A hiba csak a fórum szekcióban jelentkezik.)","replies":[{"poster":"Demon of Plague","date":"2016-11-08T11:49:14.723+0000","up_votes":1,"down_votes":1,"body":"Nekem chrommal szuperül megy minden","replies":[{"poster":"Orvvadasz1","date":"2016-11-08T12:27:45.175+0000","up_votes":2,"down_votes":1,"body":"Telefon!","replies":[{"poster":"derX","date":"2016-11-08T17:00:27.901+0000","up_votes":2,"down_votes":0,"body":"***","replies":[{"poster":"Demon of Plague","date":"2016-11-10T15:16:25.499+0000","up_votes":1,"down_votes":0,"body":"Nekem a telómon chrome van tehát\n pejparipapimpilimpijeapopódba","replies":[]}]}]}]},{"poster":"derX","date":"2016-11-08T11:47:47.773+0000","up_votes":1,"down_votes":1,"body":"***","replies":[{"poster":"Orvvadasz1","date":"2016-11-08T12:28:08.447+0000","up_votes":2,"down_votes":1,"body":"Telefon!","replies":[{"poster":"kalamona90","date":"2016-11-08T17:40:27.112+0000","up_votes":1,"down_votes":0,"body":"> [{quoted}](name=Orvvadasz1,realm=EUNE,application-id=YzZuykbk,discussion-id=0k4Bz99X,comment-id=00000000,timestamp=2016-11-08T12:28:08.447+0000)\n>\n> Telefon!\n\nTehát pusztán azért mert telefon ne is működjön jól???","replies":[]}]}]},{"poster":"alkohol23","date":"2016-11-08T17:57:15.774+0000","up_votes":1,"down_votes":0,"body":"Ha a felkiáltójel alatt a \"játék állapotának megtekintésére\" gondolsz, ahol leírják, hogy miújság pl a szerverekkel, épp kivettek egy hőst, vagy kivették a rangsorolt várolistát, akkor jól értettem a dolgot :)\nA hiba nálam is fenn áll, és nálam is csak a fórum szekcióban. Viszont ha elforgatom a telefont (fekvő állapotba helyezem), akkor jól jelenik meg.\niPhone 6S - **Safari**,**Chrome**,**Dolphin **böngészőkben próbáltam.\nA hiba nem annyira zavaró, de ahogy egy barátom mondani szokta: _Na de hee_ :)","replies":[]},{"poster":"kalamona90","date":"2016-11-08T11:58:15.973+0000","up_votes":1,"down_votes":0,"body":"Nekem se a legjobb. (winfos 10 telefonon)","replies":[]}]} |
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{"poster":"BROKEN SWIFT","date":"2018-11-17T11:42:51.484+0000","title":"Mitspieler für ARAM","subforum":"Clans & Teams","up_votes":1,"down_votes":0,"body":"Wer lust auf ein paar Runden ARAM hat, einfach BROKEN SWIFT adden :D\r\n\r\nsee yaa in the lobby :D","replies":[]} |
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{"paper": {"title": "Improving Differentially Private Models with Active Learning", "authors": ["Zhengli Zhao", "Nicolas Papernot", "Sameer Singh", "Neoklis Polyzotis", "Augustus Odena"], "authorids": ["zhengliz@uci.edu", "papernot@google.com", "sameer@uci.edu", "npolyzotis@google.com", "augustusodena@google.com"], "summary": "We introduce privacy-aware active learning techniques to improve differentially private classifiers and achieve state-of-the-art results.", "abstract": "Broad adoption of machine learning techniques has increased privacy concerns for models trained on sensitive data such as medical records. Existing techniques for training differentially private (DP) models give rigorous privacy guarantees, but applying these techniques to neural networks can severely degrade model performance. This performance reduction is an obstacle to deploying private models in the real world. In this work, we improve the performance of DP models by fine-tuning them through active learning on public data. We introduce two new techniques - DiversePublic and NearPrivate - for doing this fine-tuning in a privacy-aware way. For the MNIST and SVHN datasets, these techniques improve state-of-the-art accuracy for DP models while retaining privacy guarantees.", "keywords": ["Differential Privacy", "Active Learning"]}, "meta": {"decision": "Reject", "comment": "This paper provides an active-learning approach to improve the performance of an existing differentially private classifier with public labeled data. Where the paper provides a new approach, there is a consensus among the reviewers that the paper does not provide a strong enough contribution for acceptance. The authors can potentially improve the submission by including a more comprehensive comparison with the PATE framework and improving its overall presentation."}, "review": {"S1eIEPFXcS": {"type": "review", "replyto": "HylcapVtvB", "review": "---SUMMARY---\nThis paper gives two methods for improving an existing differentially private model. Both methods assume a source of unlabeled data that requires no privacy guarantees. The two methods make different uses of this public data to augment the original private model. Both preserve (a degree of) privacy for the original model.\n\nThe first method is DiversePublic. DiversePublic only post-processes the original private model M -- in particular, it does not touch the original data -- and so its privacy is immediate. At a high level, DiversePublic works by picking the \"best\" unlabelled data points for augmenting M. First, it applies M to the unlabeled data and then applies PCA to the result. Next, it selects highly \"uncertain\" points, projects them onto the top k principal components, and clusters the results. Finally, it selects samples from each cluster and uses them to augment M. This augmenting process, called FineTune, is left as a black box.\n\nThe second method is NearPrivate. The given motivation for NearPrivate is that the public dataset may have a different distribution than the original private training data. To address this, NearPrivate uses DP-PCA (a pre-existing technique for differentially private PCA) on the private dataset and projects both the private and public data onto the top k principal components. Then it compares uncertain points in the public and private dataset projections and only augments M (again using the black box FineTune) using uncertain public examples with many nearby uncertain private samples. Intuitively, this should select for points that are not too different than the original private training data.\n\nThe paper then evaluates these algorithms with experiments on MNIST and SVHN under reasonable privacy parameters (I think -- see below). These experiments compare the performance of DiversePublic and NearPrivate, where both train M using vanilla DP-SGD [Abadi et al. 2016]. DiversePublic and NearPrivate trade performances on MNIST and SVHN, but NearPrivate does (as might be expected) better when the public dataset is polluted.\n\nIn summary, the paper suggests DiversePublic and NearPrivate as useful ways to augment a given differentially private model M using public data, and their experiments suggest this is reasonable.\n\n---DECISION---\nReject.\n\nThis is an empirical paper. It proposes some algorithms and justifies these algorithms through experiments. However, the paper makes a confusing omission: it does not mention PATE [1, 2].\n\n[1] \"Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data\". Papernot et al. 2017.\n[2] \"Scalable Learning with PATE\". Papernot et al. 2018.\n\nI am more of a pure differential privacy researcher and am therefore less familiar with this line of mostly empirical work. But as far as I can tell PATE works in the same setting as that of this paper: there is a private dataset, a public unlabelled dataset, and the goal is to train a model with a differential privacy guarantee for the private dataset. As a result, PATE seems directly relevant. In particular, the claim that \"there are no published examples of a differentially private SVHN classifier with both reasonable accuracy and non-trivial privacy guarantees\" seems wrong, as the PATE papers include just that.\n\nMoreover, PATE appears at least competitive with the algorithms here. For example, the comparison given as Table 1 in [2] suggests that PATE can get 98-99% accuracy on MNIST for privacy parameters at least as low as those used here with only a few hundred new labelings. In contrast, if I understand the experiments here, they are using thousands of new labelled examples to get the same accuracy and privacy. Similarly, on SVHN the experiments here get to 84% accuracy with 10,000 new labelled examples, whereas the same Table 1 puts PATE at 90% with almost identical privacy parameters and thousands fewer new labelled examples.\n\nThat comparison is my main concern. Perhaps I am missing a reason why PATE is not comparable. If it is, it should certainly appear in the experiments. If PATE is indeed comparable, then the main improvement contributed by this paper is the post-processing aspect: PATE is a way to train a private model from scratch, but these methods work on an existing model. Even then, the question of how exactly the existing model is modified (the FineTune method) is unclear.\n\nMore broadly, there are several parts of this paper that could be much clearer. I am sympathetic to paper length limitations, but I am certain many or all of these issues can be addressed in 8 pages.\n\n1. DiversePublic description: What does it mean to \"obtain the 'embeddings'...E_{public}\"? How is k picked?\n2. How does the private point-public point assignment in NearPrivate work? Is it just random? How many points do we pick? \n3. In general, how is FineTune meant to work? I understand it is meant to be an abstract black box in the algorithm descriptions, but the experiment description doesn't explain it either. How does FineTune work in the experiments?\n4. What does 'headroom' mean in Section 4.2?\n5. The way privacy parameters are specified at various points in the experiment section makes things hard to read. A concise table summarizing privacy parameters, accuracy, and additional labels would help.\n\nBut overall, I am most interested in the PATE comparison. \n\n---EDIT AFTER AUTHOR RESPONSE---\nI missed the data-dependent aspect of PATE's privacy guarantee. That is a point in favor of this paper. As such, I've increased my score from reject to weak reject.\n\nI actually think a revised version of this paper could reasonably appear in ICLR or similar venues. However, I think the necessary revisions are too large/numerous to accept the paper in its current form, even with promises of revisions. Here are a few revisions that I think would make the paper a much better submission to future conferences:\n\n1. Add discussion of PATE. The data-dependence of their privacy guarantees is well-taken. But it is not clear that data-dependent privacy guarantees are as \"trivial\" as the paper currently claims with \"there are no published examples of a differentially private SVHN classifier with both reasonable accuracy and non-trivial privacy guarantees\" suggests. (In fact, I find it confusing that one of the PATE authors agrees with this claim -- they think their own work is trivial?). I agree that data-independent privacy guarantees are preferable, but this should certainly be discussed. As the authors themselves note, the original PATE paper was well-received, so if this paper wants to claim its privacy guarantees are somehow meaningless or even just unsatisfactory, that claim needs to be defended.\n\n2. Elaborate on the fine-tuning process. Perhaps \"fine tuning\" is indeed \"super standard in the object recognition literature\", but as all three reviews here indicate, the presentation of fine tuning is unclear in this paper. The author responses also seem to simultaneously claim that fine tuning is both \"super standard\" and \"[not] obvious\". \n\n3. To make room for the text above, it's not clear that the material about data pollution or even presenting both methods is necessary. I would prefer to see a thorough explanation of the active learning/post-processing paradigm through one algorithm. The authors seem to want to claim that active learning is a useful private approach because it gets data-independent privacy guarantees and performance similar to algorithms with data-dependent privacy guarantees. A paper that focuses on and thoroughly defends that claim actually sounds pretty good! ", "title": "Official Blind Review #4", "rating": "3: Weak Reject", "confidence": 3}, "SyeBQaY3sH": {"type": "rebuttal", "replyto": "r1lWF5EAYS", "comment": "Hi, responses inline, for posterity:\n\n> It neither makes core contributions to differential privacy nor to active learning.\nSee our response to Reviewer 4 on this point.\n\n> Arguably the main contribution of the paper is the heuristics for selecting public instances for fine-tuning.\nWe would argue that the main contribution is showing that simple techniques can substantially improve the\nstate of the art for differentially private classifiers, but again, see our response to reviewer 4.\n\n> do not clearly outperform baseline acquisition functions \nFirst, figures 1 and 2 clearly show that they do outperform the baseline acquisition functions,\nso we're slightly confused by this comment?\nSecond, and more importantly, the baselines are (again see our response to R4) baselines we establish in this paper.\nThere was no prior literature on using active learning for this purpose,\nand we claim that establishing those baselines is one of the main contributions of this paper.\n\n> Finally, I am unconvinced that the paper\u2019s premise of having access to related public data is realistic.\nThis is the main premise of [1], one of the most highly-cited papers in this subfield and an Oral presentation\nat ICLR 2017.\n\n[1] \"Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data\". Papernot et al. 2017.\n( https://openreview.net/forum?id=HkwoSDPgg )\n", "title": "Hi"}, "ByeD__KhsS": {"type": "rebuttal", "replyto": "S1eIEPFXcS", "comment": "Responses to your numbered questions:\n\n1. These are just the activations for the second to last layer of the classifier.\nThis terminology is pretty common in the object recognition literature.\nk is chosen with standard hyper-parameter optimization.\n\n2. From the text:\n'we assign each uncertain private example to exactly one uncertain public\nexample according to Euclidean distance'\n\n3. Sorry for the confusion here: 'Fine-tuning' as a term is also super standard in the object\nrecognition literature: it means that you take a trained model and update its weights using\nnew data. Generally, it's understood that you use a lower learning rate, and perhaps 'freeze'\nsome of the weights of the earlier layers of the neural network.\n\n4. Just that SVHN accuracy benchmarks are further from being saturated than MNIST ones.\n\n5. Understood. \n", "title": "Responses to your numbered questions:"}, "B1etAUK2oH": {"type": "rebuttal", "replyto": "ryxQH_TlsH", "comment": "Thanks for updating your review regarding the bounds.\nFor posterity, we respond to your other points:\n\n> I do not think this paper has made a lot of contribution to either differential privacy or active learning.\nYes, we are not claiming to have made such contributions.\nWhat we claim is having presented a way to substantially reduce the gap between differentially private classifiers and normal classifiers:\n\nIf you want to actually use differentially private classifiers in real life, you will be sad,\nbecause the accuracy will be poor. \nWe point out that you can improve accuracy substantially by fine-tuning on public data after the fact.\nThis is already something that was not in the literature. \nI don't think you can credibly claim that it's 'obvious' that fine-tuning on a totally different data-set\nafter the fact will improve performance on your test set;\nthis is not what anyone uses fine-tuning for currently.\nWe also give two algorithms for doing this fine-tuning (both of which are new, by the way), and we give\na privacy analysis for the algorithm that needs it.\n\n> There is almost no theoretical contribution made by this paper.\nYes, this is not a theory paper.\nThis is not a theory conference either.\n\n> Besides, from the experimental perspective, neither can I see an obvious improvement compared with the benchmarks.\nWe increase the state-of-the-art for differentially private MNIST from 97.5% to 98.8%. \nExperimentally, that's a significant jump - it's more than a halving in error-rate.\nThe improvement in SVHN is even more significant.\nPerhaps some of the confusion here is around benchmarks:\nMost of the benchmarks in the paper are in fact *benchmarks that we have set in this paper*.\nWe claim that a paper that only pointed out how helpful fine-tuning can be for DP classifiers\nwould, by itself, be worth publishing; we have written such a paper, and then added even more things.\n", "title": "Thanks for updating your review."}, "ryxQH_TlsH": {"type": "review", "replyto": "HylcapVtvB", "review": "This paper considers the problem of how to improve the performance of an existing DP classifier, with the help of the labelled public data. The paper considers the following process: 1. find a public dataset containing relevant samples; 2. carefully select a subset of public samples that can improve the performance of the classifier; 3 fine-tune the existing classifier on the selected samples. Two different techniques from active learning are utilized in order to select representative samples from a public dataset and fine-tune a DP classifier. This paper also conducts some experiments on the MNIST and SVHN datasets and demonstrates improvement compared with the benchmark.\n\nI vote for rejecting for this paper, because of the following two concerns:\n\n1. I do not think this paper has made a lot of contribution to either differential privacy or active learning. It just \"borrows\" some fine-tuning techniques from active learning and apply it in DP. There is almost no theoretical contribution made by this paper. Besides, from the experimental perspective, neither can I see an obvious improvement compared with the benchmarks.\n\n2. I do not think the privacy analysis of the NearPrivate algorithm (Algorithm 2) is correct. The paper uses private argmax algorithm and claims that it satisfies $eps_{support}$-DP. However, this is only true when $N_{labeled} = 1$. Generally, it should satisfy $eps_{support} \\cdot N_{labeled}$-DP. So if we look at the experimental setting of MNIST, roughly thousand times less noise is added! Since this amount of noise is non-trivial at all, I can not judge the effectiveness of the algorithm.\n------------------------------------------------------------------------------------------\nThanks for the authors' classification. I missed the part that each private sample was only assigned to one public sample. Now I can confirm the correctness of the algorithm and increase my score accordingly.", "title": "Official Blind Review #5", "rating": "3: Weak Reject", "confidence": 3}, "HyeyNe0sir": {"type": "rebuttal", "replyto": "ryxQH_TlsH", "comment": "We wish to clarify why the sampling procedure of our NearPrivate method is differentially private with cost $\\varepsilon_{support}$. \n\nFor each uncertain private example, we assign it to one and only one uncertain public example according to Euclidean distance. For each uncertain public example, this yields a count $N_{support}$ of how many uncertain private examples are 'nearby'. This count $N_{support}$ has sensitivity of 1 with regard to each uncertain private example. We add LaplaceNoise(1/$\\varepsilon_{support}$) to this count $N_{support}$, and sample from the uncertain public data according to the noisy $N_{support}$. This sampling procedure is differentially private with cost $\\varepsilon_{support}$ due to the Laplace mechanism [1].\n\n[1] \"The algorithmic foundations of differential privacy\". Dwork and Roth. 2014.", "title": "Thanks for the review!"}, "ryxbwtc7iS": {"type": "rebuttal", "replyto": "S1eIEPFXcS", "comment": "We are working on a more thorough response, but in the meantime we wanted to clarify:\n\nThere is indeed a reason why PATE is not comparable:\nThe bounds for PATE are data-dependent, unlike the bounds for DP-SGD.\nSee Section 3.3 of [1] for more on this.\nData-independent bounds for PATE would be much higher.\nWe double checked this with an author of [2].\n\nWe actually ran the claim \"there are no published examples of a differentially private SVHN classifier with both reasonable accuracy and non-trivial privacy guarantees\" by one of the PATE paper authors before submission and they were OK with it.\n\nSorry for the confusion on this point, we should have been much more clear about it in the paper.\n\n\n[1] \"Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data\". Papernot et al. 2017.\n[2] \"Scalable Learning with PATE\". Papernot et al. 2018.\n\n", "title": "Thanks for the review!"}, "r1lWF5EAYS": {"type": "review", "replyto": "HylcapVtvB", "review": "The paper proposes methods for improving the performance of differentially private models when additional related but public data is available. The authors propose to fine-tune the private model with related but public data. Two heuristics for selecting data to fine-tune with are presented. \n\nI vote for rejecting the paper. My main concerns revolve around the paper's contributions. It neither makes core contributions to differential privacy nor to active learning. What it does instead is present a post-processing procedure which boils down to fine-tuning differentially private models with public data. Arguably the main contribution of the paper is the heuristics for selecting public instances for fine-tuning. These rely on several design choices (why k-means? how are points from within a cluster sampled -- uniformly at random, some other heuristic? how are uncertain private and public points matched, by solving an assignment problem or something else? ) that are not well justified or have missing details and more importantly do not clearly outperform baseline acquisition functions - selecting points based on predictive entropy or the difference between two largest logits. Finally, I am unconvinced that the paper\u2019s premise of having access to related public data is realistic. \n\nThis would likely not change my opinion of the paper, but it would be good to substantiate the claims made in the second paragraph of the paper \u2014 the performance of differentially private models degrades with increasing model size. If the relationship is as clear as the paragraph makes it sound, then it would be great to include a graph with the x-axis being the number of parameters and the y-axis being the difference in performance between a regular and a differentially private model. One would expect to see the difference increase with model size.", "title": "Official Blind Review #2", "rating": "1: Reject", "confidence": 2}, "HkxbFokhPr": {"type": "rebuttal", "replyto": "H1xBWBTcDH", "comment": "You're missing an important fact about differential privacy, which is that it is 'immune to post processing'[1].\nIn this case, the original DP-SGD training procedure is a DP algorithm that returns parameters of a model.\nWithout access to the original private training data, you can't compute any function of those parameters that reduces the original privacy guarantee. \n\nIn general, fine-tuning the DP model on public data *is* computing a function of the original parameters that doesn't reference the private training data.\nWe do include a technique in the paper that references the private training data during fine-tuning, but in that case we compute the privacy cost of these references. \n\n[1] https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf\n", "title": "DP algorithms are immune to post-processing."}}} |
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{"data":[{"card_id":"EX1_562","cost":9,"set":"CLASSIC","format":"STANDARD","faction":"NEUTRAL","type":"MINION","rarity":"LEGENDARY","race":"DRAGON","collectible":true,"text":"<b>Battlecry:</b> Summon 1/1 Whelps until your side of the battlefield is full.","name":"Onyxia","card_slug":"onyxia","artist":"Dany Orizio","flavor_text":"Onyxia long manipulated the Stormwind Court by disguising herself as Lady Katrana Prestor. You would have thought that the giant wings and scales would have been a giveaway.","card_class":"NEUTRAL","mechanics":["BATTLECRY"],"attack":8,"health":8,"legacy_card_id":363,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/EX1_562.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/EX1_562.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/EX1_562_premium.gif"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_EX1_562_Attack_03.ogg"},{"type":"OTHER_SOUND","url":"/hs/sounds/enus/Pegasus_Stinger_Deathwing.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_EX1_562_Death_04.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_EX1_562_Play_01.ogg"},{"type":"TRIGGER_SOUND","url":"/hs/sounds/enus/VO_EX1_562_Trigger_02.ogg"}]},
{"card_id":"OG_340","cost":9,"set":"OG","format":"STANDARD","type":"MINION","rarity":"LEGENDARY","collectible":true,"text":"<b>Taunt</b>\nCan't be targeted by spells or Hero Powers.","name":"Soggoth the Slitherer","card_slug":"soggoth-the-slitherer","artist":"James Ryman","flavor_text":"Don't tell Soggoth, but in the future he gets totally owned by the Master's Glaive and his skull becomes a tourist attraction.","card_class":"NEUTRAL","mechanics":["TAUNT"],"attack":5,"health":9,"legacy_card_id":39119,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/OG_340.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/OG_340.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/OG_340_premium.gif"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_OG_340_Male_Faceless_Death_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_340_Male_Faceless_Play_01.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_OG_340_Male_Faceless_Attack_01.ogg"}]},
{"card_id":"GVG_033","cost":9,"set":"GVG","format":"WILD","type":"SPELL","rarity":"EPIC","collectible":true,"text":"Restore all characters to full Health.","name":"Tree of Life","card_slug":"tree-of-life","artist":"Steve Prescott","flavor_text":"Healing: It grows on trees!","card_class":"DRUID","legacy_card_id":2001,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/GVG_033.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/GVG_033.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/GVG_033_premium.gif"}]},
{"card_id":"BRM_009","cost":9,"set":"BRM","format":"STANDARD","type":"MINION","rarity":"RARE","collectible":true,"text":"<b>Taunt</b>\nCosts (1) less for each minion that died this turn.","name":"Volcanic Lumberer","card_slug":"volcanic-lumberer","artist":"Trent Kaniuga","flavor_text":"The roots, the roots, the roots is on fire!","how_to_earn":"Unlocked in Blackrock Spire, in the Blackrock Mountain adventure.","how_to_earn_golden":"Crafting unlocked in Blackrock Spire, in the Blackrock Mountain adventure.","card_class":"DRUID","mechanics":["TAUNT"],"attack":7,"health":8,"legacy_card_id":2295,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/BRM_009.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/BRM_009.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/BRM_009_premium.gif"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/BRM_009_VolcanicLumberer_Attack_1.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/BRM_009_VolcanicLumberer_Death_1.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/BRM_009_VolcanicLumberer_Play_1.ogg"}]},
{"card_id":"EX1_572","cost":9,"set":"CLASSIC","format":"STANDARD","faction":"NEUTRAL","type":"MINION","rarity":"LEGENDARY","race":"DRAGON","collectible":true,"text":"At the end of your turn, add a Dream Card to your hand.","name":"Ysera","card_slug":"ysera","artist":"Gabor Szikszai","flavor_text":"Ysera rules the Emerald Dream. Which is some kind of green-mirror-version of the real world, or something?","card_class":"NEUTRAL","attack":4,"health":12,"legacy_card_id":1186,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/EX1_572.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/EX1_572.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/EX1_572_premium.gif"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_EX1_572_Attack_02.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_EX1_572_Death_03.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_EX1_572_Play_01.ogg"}],"entourage_card_ids":["DREAM_01","DREAM_02","DREAM_03","DREAM_04","DREAM_05"]},
{"card_id":"LOE_026","cost":10,"set":"LOE","format":"STANDARD","type":"SPELL","rarity":"RARE","collectible":true,"text":"Summon 7 Murlocs that died this game.","name":"Anyfin Can Happen","card_slug":"anyfin-can-happen","artist":"Ryan Metcalf","flavor_text":"Theme song by Ellie Goldfin and Blagghghlrlrl Harris.","how_to_earn":"Unlocked in The Ruined City, in the League of Explorers adventure.","how_to_earn_golden":"Crafting unlocked in The Ruined City, in the League of Explorers adventure.","card_class":"PALADIN","legacy_card_id":2898,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/LOE_026.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/LOE_026.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/LOE_026_premium.gif"}]},
{"card_id":"OG_280","cost":10,"set":"OG","format":"STANDARD","type":"MINION","rarity":"LEGENDARY","collectible":true,"text":"<b>Battlecry:</b> Deal damage equal to this minion's Attack randomly split among all enemies.","name":"C'Thun","card_slug":"cthun-1","artist":"James Ryman","flavor_text":"C'Thun's least favorite Hearthstone card: Eye for an Eye.","how_to_earn":"Unlocked when opening a Whispers of the Old Gods pack.","how_to_earn_golden":"Crafting unlocked after opening a Whispers of the Old Gods pack.","card_class":"NEUTRAL","mechanics":["BATTLECRY"],"attack":6,"health":6,"legacy_card_id":38857,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/OG_280.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/OG_280.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/OG_280_premium.gif"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_Play_01.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_Death_01.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_Attack_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_02.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_03.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_06.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_07.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_04.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_05.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_08.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_09.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_10.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_11.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_280_Male_OldGod_InPlay_12.ogg"}]},
{"card_id":"OG_239","cost":10,"set":"OG","format":"STANDARD","type":"SPELL","rarity":"EPIC","collectible":true,"text":"Destroy all minions. Draw a card for each.","name":"DOOM!","card_slug":"doom","artist":"Raymond Swanland","flavor_text":"We ran out of space for \"DOOOOOOOOOOOM!!!!!\"","card_class":"WARLOCK","legacy_card_id":38770,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/OG_239.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/OG_239.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/OG_239_premium.gif"}]},
{"card_id":"NEW1_030","cost":10,"set":"CLASSIC","format":"STANDARD","type":"MINION","rarity":"LEGENDARY","race":"DRAGON","collectible":true,"text":"<b>Battlecry:</b> Destroy all other minions and discard your hand.","name":"Deathwing","card_slug":"deathwing","artist":"Bernie Kang","flavor_text":"Once a noble dragon known as Neltharion, Deathwing lost his mind and shattered Azeroth before finally being defeated. Daddy issues?","card_class":"NEUTRAL","mechanics":["BATTLECRY"],"attack":12,"health":12,"legacy_card_id":834,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/NEW1_030.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/NEW1_030.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/NEW1_030_premium.gif"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_NEW1_030_Play_01.ogg"},{"type":"OTHER_SOUND","url":"/hs/sounds/enus/Pegasus_Stinger_Deathwing3.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_NEW1_030_Attack_02.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_NEW1_030_Death_03.ogg"}]},
{"card_id":"OG_317","cost":10,"set":"OG","format":"STANDARD","type":"MINION","rarity":"LEGENDARY","race":"DRAGON","collectible":true,"text":"<b>Deathrattle:</b> Put all Dragons from your hand into the battlefield.","name":"Deathwing, Dragonlord","card_slug":"deathwing-dragonlord","artist":"Alex Horley Orlandelli","flavor_text":"To his credit, Deathwing really took to heart the feedback he was receiving that he needed to be \"more of a team player\".","card_class":"NEUTRAL","mechanics":["DEATHRATTLE"],"attack":12,"health":12,"legacy_card_id":38943,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/OG_317.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/OG_317.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/OG_317_premium.gif"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_317_Male_Dragon_Play_01.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_OG_317_Male_Dragon_Death_01.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_OG_317_Male_Dragon_Attack_01.ogg"}]},
{"card_id":"OG_141","cost":10,"set":"OG","format":"STANDARD","type":"MINION","rarity":"COMMON","collectible":true,"name":"Faceless Behemoth","card_slug":"faceless-behemoth","artist":"Zoltan Boros","flavor_text":"Rejected names: Forty-Foot Faceless, Big ol' No-face, Huge Creature Sans Face, Teddy.","card_class":"NEUTRAL","attack":10,"health":10,"legacy_card_id":38521,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/OG_141.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/OG_141.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/OG_141_premium.gif"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_OG_141_Androgynous _Faceless_Death_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_141_Androgynous _Faceless_Play_01.ogg"}]},
{"card_id":"AT_120","cost":10,"set":"TGT","format":"STANDARD","type":"MINION","rarity":"EPIC","collectible":true,"text":"Costs (1) less for each time you used your Hero Power this game.","name":"Frost Giant","card_slug":"frost-giant","artist":"Greg Staples","flavor_text":"Don't ask him about the beard. JUST DON'T.","card_class":"NEUTRAL","attack":8,"health":8,"legacy_card_id":2512,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/AT_120.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/AT_120.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/AT_120_premium.gif"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/SFX_AT_120_Attack_01.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/SFX_AT_120_Death_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/SFX_AT_120_Play_01.ogg"}]},
{"card_id":"CFM_308","cost":10,"set":"GANGS","format":"STANDARD","type":"MINION","rarity":"LEGENDARY","collectible":true,"text":"<b>Choose One -</b> Gain 10 Armor; or Refresh your Mana Crystals.","name":"Kun the Forgotten King","card_slug":"kun-the-forgotten-king","artist":"Jon Neimeister","flavor_text":"Aya siphons a bit of Kun's soul to animate each golem in her Jade army. To his credit, he's being a great sport about it.","card_class":"DRUID","mechanics":["CHOOSE ONE"],"attack":7,"health":7,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/CFM_308.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/CFM_308.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/CFM_308_premium.gif"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_CFM_308_Male_Mogu_Death_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_CFM_308_Male_Mogu_Play_01.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_CFM_308_Male_Mogu_Attack_01.ogg"}]},
{"card_id":"CS1_113","cost":10,"set":"BASIC","format":"STANDARD","faction":"NEUTRAL","type":"SPELL","rarity":"COMMON","collectible":true,"text":"Take control of an enemy minion.","name":"Mind Control","card_slug":"mind-control","artist":"Sean O’Daniels","flavor_text":"Nominated as \"Spell Most Likely to Make Your Opponent Punch the Wall.\"","how_to_earn":"Unlocked at Level 10.","how_to_earn_golden":"Unlocked at Level 49.","card_class":"PRIEST","legacy_card_id":8,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/CS1_113.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/CS1_113.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/CS1_113_premium.gif"}]},
{"card_id":"OG_133","cost":10,"set":"OG","format":"STANDARD","type":"MINION","rarity":"LEGENDARY","collectible":true,"text":"<b>Battlecry:</b> Summon your <b>Deathrattle</b> minions that died this game.","name":"N'Zoth, the Corruptor","card_slug":"nzoth-the-corruptor","artist":"Tyson Murphy","flavor_text":"Has not been able to get \"Under the Sea\" out of his head for like FIVE THOUSAND YEARS.","card_class":"NEUTRAL","mechanics":["BATTLECRY","DEATHRATTLE"],"attack":5,"health":7,"legacy_card_id":38496,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/OG_133.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/OG_133.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/OG_133_premium.gif"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_OG_133_Male_OldGod_Death_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_284_Female_Orc_Play_01.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/KARA_13_22_Mime_Death.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_OG_042_Male_OldGod_Death_01.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_OG_133_Male_OldGod_Attack_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_133_Male_OldGod_Play_01.ogg"}]},
{"card_id":"EX1_279","cost":10,"set":"CLASSIC","format":"STANDARD","faction":"NEUTRAL","type":"SPELL","rarity":"EPIC","collectible":true,"text":"Deal 10 damage.","name":"Pyroblast","card_slug":"pyroblast","artist":"Luca Zontini","flavor_text":"Take the time for an evil laugh after you draw this card.","card_class":"MAGE","legacy_card_id":1087,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/EX1_279.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/EX1_279.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/EX1_279_premium.gif"}]},
{"card_id":"EX1_586","cost":10,"set":"CLASSIC","format":"STANDARD","faction":"NEUTRAL","type":"MINION","rarity":"EPIC","collectible":true,"text":"Costs (1) less for each other minion on the battlefield.","name":"Sea Giant","card_slug":"sea-giant","artist":"Svetlin Velinov","flavor_text":"See? Giant.","card_class":"NEUTRAL","attack":8,"health":8,"legacy_card_id":211,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/EX1_586.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/EX1_586.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/EX1_586_premium.gif"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/SFX_EX1_586_Attack.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/SFX_EX1_586_Death.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/SFX_EX1_586_EnterPlay.ogg"}]},
{"card_id":"AT_072","cost":10,"set":"TGT","format":"STANDARD","type":"MINION","rarity":"LEGENDARY","collectible":true,"text":"<b>Battlecry:</b> Draw 3 cards.\nPut any minions you drew directly into the battlefield.","name":"Varian Wrynn","card_slug":"varian-wrynn","artist":"Wei Wang","flavor_text":"Leader of the Alliance! Father of Anduin! Also he likes to play Arena, and he averages 12 wins.","card_class":"WARRIOR","mechanics":["BATTLECRY"],"attack":7,"health":7,"legacy_card_id":2760,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/AT_072.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/AT_072.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/AT_072_premium.gif"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_AT_072_ATTACK_03.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_AT_072_DEATH_04.ogg"},{"type":"OTHER_SOUND","url":"/hs/sounds/enus/VO_AT_072_ANDUIN_ALT3_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_AT_072_PLAY_01.ogg"}]},
{"card_id":"OG_042","cost":10,"set":"OG","format":"STANDARD","type":"MINION","rarity":"LEGENDARY","collectible":true,"text":"At the end of your turn, put a minion from your deck into the battlefield.","name":"Y'Shaarj, Rage Unbound","card_slug":"yshaarj-rage-unbound","artist":"Samwise","flavor_text":"When he's working out, he binds all that rage back into a ponytail.","card_class":"NEUTRAL","attack":10,"health":10,"legacy_card_id":38312,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/OG_042.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/OG_042.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/OG_042_premium.gif"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_042_Male_OldGod_Play_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/VO_OG_254_Androgynous _Faceless_Play_01.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_KAR_061_Male_ArcaneGolem_Death_02.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_OG_133_Male_OldGod_Play_01.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/VO_OG_042_Male_OldGod_Attack_01.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/VO_OG_042_Male_OldGod_Death_01.ogg"}]},
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{"card_id":"KAR_711","cost":12,"set":"KARA","format":"STANDARD","type":"MINION","rarity":"EPIC","collectible":true,"text":"Costs (1) less for each spell\nyou've cast this game.","name":"Arcane Giant","card_slug":"arcane-giant","artist":"Dan Scott","flavor_text":"Claims to be drawn to Karazhan because of the ley lines. Actually, just loves Moroes’ cooking.","how_to_earn":"Unlocked in the Opera, in One Night in Karazhan.","how_to_earn_golden":"Crafting unlocked in the Opera, in One Night in Karazhan.","card_class":"NEUTRAL","attack":8,"health":8,"legacy_card_id":39426,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/KAR_711.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/KAR_711.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/KAR_711_premium.gif"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/KAR_711_ArcaneGiant_Death_01.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/KAR_711_ArcaneGiant_Attack_01.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/KAR_711_ArcaneGiant_Play_01.ogg"}]},
{"card_id":"GVG_121","cost":12,"set":"GVG","format":"WILD","type":"MINION","rarity":"EPIC","race":"MECH","collectible":true,"text":"Costs (1) less for each card in your opponent's hand.","name":"Clockwork Giant","card_slug":"clockwork-giant","artist":"Dan Scott","flavor_text":"He and Mountain Giant don't get along.","card_class":"NEUTRAL","attack":8,"health":8,"legacy_card_id":2233,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/GVG_121.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/GVG_121.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/GVG_121_premium.gif"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/SFX_GVG_121_Attack.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/SFX_GVG_121_Death.ogg"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/SFX_GVG_121_EnterPlay.ogg"}]},
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{"card_id":"EX1_620","cost":25,"set":"CLASSIC","format":"STANDARD","type":"MINION","rarity":"EPIC","collectible":true,"text":"Costs (1) less for each damage your hero has taken.","name":"Molten Giant","card_slug":"molten-giant","artist":"Glenn Rane","flavor_text":"He gets terrible heartburn. BECAUSE HE IS FULL OF LAVA.","card_class":"NEUTRAL","attack":8,"health":8,"legacy_card_id":1372,"media":[{"type":"DB_CARD_IMAGE","url":"/hs/cards/enus/pal/EX1_620.png"},{"type":"CARD_IMAGE","url":"/hs/cards/enus/EX1_620.png"},{"type":"GOLDEN_CARD_IMAGE","url":"/hs/cards/enus/animated/EX1_620_premium.gif"},{"type":"PLAY_SOUND","url":"/hs/sounds/enus/EX1_620_Molten_Giant_EnterPlay2.ogg"},{"type":"ATTACK_SOUND","url":"/hs/sounds/enus/EX1_620_Molten_Giant_Attack1.ogg"},{"type":"DEATH_SOUND","url":"/hs/sounds/enus/EX1_620_Molten_Giant_Death1.ogg"}]}]}
|
{"title":"【ガルパン】身魂の操縦手 -冷泉 麻子-","url":"http://blog.livedoor.jp/mode_ss/archives/52038745.html","time":"2017-03-06 01:00:45 UTC"} |
{"poster":"Subtilizer","date":"2018-11-21T19:52:59.866+0000","title":"RP ARGENTINA","subforum":"Charlas Generales","up_votes":4,"down_votes":1,"body":"RP | Dólar | Pesos\r\n----------|-----------|-----------\r\n750 | $5,00 | 181,37\r\n----------|-----------|-----------\r\n1,580 | $10,00 | 362,74\r\n----------|-----------|-----------\r\n2,430 | $15,00 | 544,11\r\n----------|-----------|-----------\r\n4,280 | $25,00 | 906,85\r\n----------|-----------|-----------\r\n8,900 | $50,00 |1,813,70\r\n--------- |-----------|-----------\r\n14,500 | $80,00 |2,901,92\r\n\r\n\r\n\r\nGG RITO GOMEZ {{sticker:slayer-pantheon-thumbs}}","replies":[{"poster":"Lord Khada","date":"2018-11-21T19:59:19.206+0000","up_votes":3,"down_votes":2,"body":"Gg rito?...naaa gg Macri","replies":[{"poster":"Mascheranox","date":"2018-11-21T20:22:33.919+0000","up_votes":1,"down_votes":0,"body":"una cosa es que aumente el RP otra cosa es que descuente los riot point,ya ni ganas te dan de comprar Rp asi","replies":[{"poster":"TvTLucio22","date":"2018-11-21T20:29:10.985+0000","up_votes":1,"down_votes":0,"body":"en realidad, es culpa de la economia argentina en los ultimos 3 años (no digo que fue POR macri, pero hace 3 años estaba mas estable y, a mediados de este año, se fue todo al carajo y el dolar paso de 28 hasta aproximadamente 40 en menos de una semana (creo que fue 3 dias realmente), so...)\n\nbajar la cantidad de rp que dan se puede entender si lo que compramos es menos a lo que compran el resto. es decir, en lugar de aumentar mucho el precio (a pagar en pesos), aumentan algo el precio (a pagar en pesos) y bajan la cantidad de rp que dan","replies":[{"poster":"Fran500","date":"2018-11-22T04:33:24.834+0000","up_votes":1,"down_votes":0,"body":"no se mucho de política, pero no creo que esto de que se vaya a la mierda pueda pasar de un momento a otro, yo creo que exploto todo por años de malas decisiones. no creo que al señor macri le guste subir el dolar a $40 porque si","replies":[{"poster":"TvTLucio22","date":"2018-11-22T05:01:44.890+0000","up_votes":2,"down_votes":0,"body":"y... convengamos que los mayores beneficiarios de la suba del dolar magicamente son los amigos y familia de macri, so...\n\nencima, las \"malas decisiones\" del pasado a las cuales dicen son las culpables de esta crisis (basicamente, todo lo que haya dicho y/o hecho cristina), tal vez no fueron las mejores, pero beneficiaron a muchos XX de los sectores sociales mas pobres (de hecho, se ayudo mucho a la clase baja y media baja). las decisiones actuales solo benefician a un grupo muy cerrado: macri, amigos y familiares del mismo, basicamente a los que quedaron de cambiemos, el grupo clarin, el sector rural (no confundir con el pobre loco que tiene un poco de tierra y se rompe el lomo laburando, sino los que tienen miles de hectareas unicamente para cultivar cosas como la soja, cuyo unico proposito es la exportacion) y, en menor medida, el sector militar. es decir, la oligarquia argentina que compone, con suerte, el 1% de la poblacion.\n\nque se yo, prefiero las malas decisiones que ayudan a por lo menos un 50% de los argentinos (y estoy siendo generoso, el sector economicamente bajo siempre es mayor que los otros 2 sectores, asi funciona la piramide poblacional)","replies":[{"poster":"Fran500","date":"2018-11-22T05:04:05.881+0000","up_votes":1,"down_votes":0,"body":"yo prefiero seguir probando que volver a algo que se que no funciono y caer en lo mismo","replies":[{"poster":"TvTLucio22","date":"2018-11-22T08:18:22.613+0000","up_votes":1,"down_votes":0,"body":"para muchos funciono, y convengamos que el modelo del kirchnerismo empezo despues de una crisis de la san puta, llevada por el \"peronista\" menem (que en realidad es neoliberal, igual que macri) y que le estallo en la cara a de la rua (que tampoco hizo mucho por detenerlo, ya que era alto inutil). que se yo, vamos apuntando al mismo camino, capaz si se aplican las mismas medidas se puede evitar una crisis tan grande y tambien salvar vidas (durante el quilombo del 2001, varias personas murieron en diversas manifestaciones reclamando trabajo, que se vaya el corralito y estabilidad economica). una vez que se vuelva a estabilizar la situacion, ahi te acepto probar algo nuevo, aunque en realidad si vas cambiando cada 4 años sin seguir una linea principal, se queda en el inicio todo ya que es construir 4 años para que venga otro a destruir lo hecho y empezar de 0, para que 4 años despues se vuelva a repetir.\n\npor otro lado, realmente no hay nadie mas que se ponga en contra de macri y que tenga alguna idea de politica (la carrio cambio de bando tantas veces que ya se perdio la cuenta (originalmente era radical y se termino aliando con macri para despues dejarlo), massa es basicamente un meme viviente, scioli ni se lo nombra, vidal es lo mismo que macri y asi seguimos)","replies":[]}]}]}]},{"poster":"L9 Skasha","date":"2018-11-22T15:09:12.931+0000","up_votes":1,"down_votes":0,"body":"> [{quoted}](name=TvTLucio22,realm=LAS,application-id=v7qsfXsE,discussion-id=VsQxEQgZ,comment-id=000000000000,timestamp=2018-11-21T20:29:10.985+0000)\n>\n> en realidad, es culpa de la economia argentina en los ultimos 3 años (no digo que fue POR macri, pero hace 3 años estaba mas estable y, a mediados de este año, se fue todo al carajo y el dolar paso de 28 hasta aproximadamente 40 en menos de una semana (creo que fue 3 dias realmente), so...)\n> \n> bajar la cantidad de rp que dan se puede entender si lo que compramos es menos a lo que compran el resto. es decir, en lugar de aumentar mucho el precio (a pagar en pesos), aumentan algo el precio (a pagar en pesos) y bajan la cantidad de rp que dan\n\nBlizzard Dijo que No Pensaba Subir los Precios a sus juegos en Argentina Porque sabe que iban a dejar de comprar. Riot Hace todo Lo Contrario.","replies":[{"poster":"TvTLucio22","date":"2018-11-22T15:33:21.895+0000","up_votes":1,"down_votes":0,"body":"Blizzard te cobra unos 60 dólares (precio estándar de un juego), ya que venden los juegos Y cosas extra como skins para el overwatch. \nEn cambio, el lol es gratis y sólo gana guita mediante la compra de rp, so...","replies":[]}]}]}]}]},{"poster":"ƒƒƒOneƒƒƒ","date":"2018-11-22T04:28:28.909+0000","up_votes":1,"down_votes":0,"body":"Esta muy barato soy de Chile compro usando de pais Argentina conviene mucho con Visa xD","replies":[]},{"poster":"larsssssssssssss","date":"2018-11-21T20:35:37.375+0000","up_votes":3,"down_votes":6,"body":"gg Macri man\nque bueno que ya se va a ir y que venga Cristina de nuevo.","replies":[{"poster":"NexusZionX","date":"2018-11-21T22:13:53.435+0000","up_votes":2,"down_votes":2,"body":"pobresito...{{sticker:sg-ezreal}}","replies":[]}]}]} |
{
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"title": "(책) 컨설팅의 비밀",
"summary": "The Secrets of Consulting by Gerald M. Weinberg",
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"url": "/wiki/secret-of-consulting",
"updated": "2021-10-04 14:06:47 +0900",
"resource": "02/752012-109C-4573-9F7A-0961219847AE",
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{"poster":"7Shad0w7","date":"2019-07-25T15:46:00.791+0000","title":"About My Perma-Ban and my experience as new player in League of Legends","subforum":"Player Behavior","up_votes":2,"down_votes":14,"body":"Listen, I recently came back from a 14-day ban which i honestly believe i deserve. To be honest If I was to be banned because of the things i said when i got my 14-day ban i would accept it. I try to improve my self every day. The things I said back when i got the 14-day ban where really bad and regret every single day for the things I said. However, the situation with my perma ban is a little diferent. To begin, YES I WAS TOXIC, but not as much as i used to be, i believe my toxicity was in the \"gamer trash talking\" range. The bot lane in my game tilted me when they started sayin \"noob\" this and \"noob\" that because my friend forgot the \"smite\" relic, so i started \"hitting\" back (ik that was a mistake). I realised my mistake though in-game and i stoped, I actually told them to \"chill\" as well, trying to improve the situation. Unfortunately, the bot laners were premade so they both reported me, plus they the enemy jgl reported me because i was \"feeding\", which is not a reason to report someone in my opinion. I know that you probaly wont change your mind but i want to let you know this, i try my best every sinlge day to spread at least some positivity to my team, but some times i slip. I recenlty started playing this game and im actualy in love with it. I wont probably continue playing though (maybe thats the best i guess) because im very sentimental with this acoount, ive invested a lot in this ( idont mean money :P) plus i was going to by my first skin (i was waiting for project pyke cuz i main him). Anyways, thank you for the experience. I just feel that i deserve a second chance, even though i wont get it. To be honest this game is the only thing that gives me joy at this moment of my life in which i had a lot of bad things to cope with, the worse of them being the hero of my life, my father passing away. League of Legends was something refershing, a chance to drift away from all the anxiety that brought my new responsibilities as the new \"head of the family\". It wont be the same starting a second account, to be honest im probably going to abbandon the game cause i was too invested with my initial account. Anyways I am going to insert my in chat game logs:\r\n\r\nGame 1\r\nPre-Game\r\n7Shad0w7: mid\r\nIn-Game\r\n7Shad0w7: gj team?\r\n7Shad0w7: are you r%%%%%ed?\r\n7Shad0w7: why gj team?\r\n7Shad0w7: ...\r\n7Shad0w7: cant stand you\r\n7Shad0w7: muted\r\n7Shad0w7: you got rekt\r\n7Shad0w7: k\r\n7Shad0w7: im wining my lane\r\n7Shad0w7: surrender\r\n7Shad0w7: ffs\r\n7Shad0w7: ...\r\n7Shad0w7: bruh\r\n7Shad0w7: youre not tyler 1 ffs\r\n7Shad0w7: wake up\r\n7Shad0w7: sona talking shit\r\n7Shad0w7: THE ENEMY SUPPORT PLAYS BETTER THAN BOTH PF YOU R%%%%%S\r\n7Shad0w7: \"feed\"\r\n7Shad0w7: since when thats a reason fucker\r\n7Shad0w7: nice engrish\r\n7Shad0w7: outplayed\r\n7Shad0w7: now stfu\r\n7Shad0w7: @rengar woosh\r\n7Shad0w7: you missed the joke r%%%%%\r\n7Shad0w7: bo\r\n7Shad0w7: no\r\n7Shad0w7: draven kys\r\n7Shad0w7: sure\r\n7Shad0w7: your mom sucks me dry every fucking day while i play fortnite\r\n7Shad0w7: still\r\n7Shad0w7: that makes your mom a ped\r\n7Shad0w7: %%%%*\r\n7Shad0w7: gj bot\r\n7Shad0w7: oof you called me kid boo hoo\r\n7Shad0w7: im not the toxic here sona\r\n7Shad0w7: tell your friend to chill\r\n7Shad0w7: ...\r\n7Shad0w7: grow up\r\n7Shad0w7: boo hoo\r\n7Shad0w7: welcome to cry.com\r\n7Shad0w7: nah\r\n7Shad0w7: im good\r\n7Shad0w7: nice items btw\r\n7Shad0w7: first time draven?\r\n7Shad0w7: ?\r\n7Shad0w7: doesnt make sense\r\n7Shad0w7: ANSER ME KID\r\n7Shad0w7: first time draven\r\n7Shad0w7: ?\r\n7Shad0w7: you suck then\r\n7Shad0w7: ok\r\n7Shad0w7: ill be the mature one\r\n7Shad0w7: too bad\r\n7Shad0w7: ?\r\n7Shad0w7: L\r\n7Shad0w7: ?\r\n7Shad0w7: dude\r\n7Shad0w7: grow up man\r\n7Shad0w7: im not toxic\r\n7Shad0w7: i just want to play the game\r\n7Shad0w7: why report me\r\n7Shad0w7: draven i tried, sorry man :)\r\n7Shad0w7: gg\r\nPost-Game\r\n7Shad0w7: ggs\r\n\r\n\r\nI know the things I said are still bad and toxic but getting the two biggest in terms of time-length bans is kinda harsh, especialy when i get reported from premade teams (both of my bans came from teammates that were friends/queued together, that means that got 3 reports each game, in the second game only the bot lane reported me). I do deserve a ban, especialy for the things I said that got me banned for 14 days but i know i can do better.","replies":[{"poster":"The Djinn","date":"2019-07-25T15:54:15.264+0000","up_votes":10,"down_votes":1,"body":">To begin, YES I WAS TOXIC, but not as much as i used to be\n\nYou insulted other players, made sexual comments about a player's mother, and told your Draven to kill himself.\n\nThis is 100% a justified permanent ban and will not be overturned. No second chance is deserved if this is how you behave *after your final warning*.","replies":[{"poster":"7Shad0w7","date":"2019-07-26T08:18:37.149+0000","up_votes":2,"down_votes":2,"body":"Understandable, thank you for your attention. Although, I believe having my first warning as a final is kinda harsh, giving the fact that i am new to League's community (which tbh is really toxic) so i couldn't adapt to that levels of toxicity in so much little time. I dont know about other regions but in EU&NE, in my elo, having a game without someone saying \"report this and that for feed etc\" and in other words harrassing people its a rare thing. Anyways, thank you for your response.","replies":[]}]},{"poster":"Arcade Lulu","date":"2019-07-25T16:01:46.011+0000","up_votes":7,"down_votes":2,"body":"On your 14 day ban report card it CLEARLY said that the next offence would lead to a permanent ban\n\nYour logs were extremely toxic. The ban is deserved\nYou getting reported by premades doesn't matter. 1 report has the same weight as 3 reports\n\nYou already got your 2nd chance after the 14 day ban, and you failed. \nYour account won't be unbanned 'cause the ban was justified","replies":[{"poster":"7Shad0w7","date":"2019-07-26T08:19:15.850+0000","up_votes":2,"down_votes":1,"body":"Ok, thanks,","replies":[]}]},{"poster":"GatekeeperTDS","date":"2019-07-25T15:49:26.838+0000","up_votes":6,"down_votes":3,"body":"> i try my best every sinlge day to spread at least some positivity to my team\n\nThat's good. Let's see how you did.\n\n> In-Game\n7Shad0w7: gj team?\n7Shad0w7: are you r%%%%%ed?\n7Shad0w7: why gj team?\n\nThe **first things you said** were flaming and insulting your team, it gets worse from there, and you have the audacity to say you're trying to improve?\n\n{{sticker:sg-lux-2}}","replies":[{"poster":"7Shad0w7","date":"2019-07-26T08:20:25.638+0000","up_votes":2,"down_votes":2,"body":"Yes I do. How can you assume my proggress from one slip up? Anyways, thanks for the tip (i guess).","replies":[{"poster":"GatekeeperTDS","date":"2019-07-26T10:50:21.629+0000","up_votes":1,"down_votes":1,"body":"We all slip up, but you're kidding yourself if you think you had \"one.\" When you get to permaban level, that ain't a slip-up, that's a pattern.","replies":[{"poster":"7Shad0w7","date":"2019-07-27T08:11:20.813+0000","up_votes":1,"down_votes":1,"body":"I had 2 slip ups. The one that got me a 14 day ban and this one.","replies":[]}]}]}]},{"poster":"Kaioko","date":"2019-07-25T19:35:50.804+0000","up_votes":3,"down_votes":2,"body":"I'm more concerned about the fact that you're supposedly \"head of the family\" which is terrifying if this is how you're raising children.","replies":[{"poster":"7Shad0w7","date":"2019-07-26T08:26:23.703+0000","up_votes":1,"down_votes":1,"body":"Ok, assuming my personality from ONE slip up in a video game, not cool man. Plus mind your own buiseness, i have to take care of my mother and my younger brother, life is sometimes tough, you dont have to make it harder with your comment.","replies":[{"poster":"Eybdoog","date":"2019-07-26T14:26:34.484+0000","up_votes":2,"down_votes":0,"body":"You are not alone. People try to pretend to be perfect. At least you’re not pretending. We all make mistakes. Just make sure you learn from them. Keep grinding!","replies":[]},{"poster":"CharDeeMcDenniz","date":"2019-07-26T10:51:31.142+0000","up_votes":1,"down_votes":1,"body":"you keep throwing up this weak \"you guys are assuming things\" excuse...i dont get it\n\nit's not really an assumption\n\nwe're forming this opinion based off the evidence you provided\n\nif we're being realistic, you claiming \"I'm not toxic I swear!!!\" while posting blatantly toxic logs is asking **US** to make an assumption about you with no evidence\n\nhmmmm....{{sticker:sg-lux-2}}","replies":[{"poster":"7Shad0w7","date":"2019-07-27T08:15:53.940+0000","up_votes":1,"down_votes":0,"body":"Ok. You won't change your mind. Belive what you want to believe, I actualy dont care. What im trying to say is dont mix up my life with my game behaviour... oh well im wasting my time with you, you could at least be somewhat helpful like the others did. Have a nice day.","replies":[]}]}]},{"poster":"Eybdoog","date":"2019-07-25T19:59:05.255+0000","up_votes":1,"down_votes":6,"body":"***","replies":[{"poster":"CharDeeMcDenniz","date":"2019-07-25T22:05:52.310+0000","up_votes":3,"down_votes":0,"body":"who the heck are you to say who can or cant post in a public forum?","replies":[{"poster":"Eybdoog","date":"2019-07-25T22:14:08.066+0000","up_votes":1,"down_votes":4,"body":"I have no authority to control it. What are you talking about?","replies":[{"poster":"CharDeeMcDenniz","date":"2019-07-25T22:18:08.691+0000","up_votes":2,"down_votes":1,"body":"ok so just trolling then, got it. bye","replies":[{"poster":"Eybdoog","date":"2019-07-25T22:34:32.869+0000","up_votes":1,"down_votes":4,"body":"Think of it as more of a recommendation than a direct order.. bye bud~~~~","replies":[]}]}]}]}]}]},{"poster":"KFCeytron","date":"2019-07-25T19:35:45.915+0000","up_votes":3,"down_votes":1,"body":"I'm sorry you've seen worse and/or I'm happy to hear that your behavior has improved, but the system wants your behavior to be _acceptable_, not just _less unacceptable_ than what you have seen in others and/or demonstrated in the past.\n\nSo, it has come to this: someone displayed misbehavior in a LoL match in flagrant disregard for the game's rules, ToS, EULA, and Summoner's Code. That's unfortunate, and I'm sorry you had to deal with it. If this misbehavior happened in chat (including emotes or ping) and they don't respond positively to a _single, courteous, constructive request to focus on the game_, your best option is to mute that player. Submit a report after the match. This is equivalent to dealing with a noisy person in a library by asking them to keep it down and then notifying library staff and moving to another area.\n\n_Do not respond with misbehavior of your own!_ If you do that, your teammates may mute and report _you_, and those reports would be valid. This is equivalent to dealing with a noisy person in a library by getting into a shouting match with them. Just because someone else started it doesn't justify you in continuing it. I'm sure you're familiar with the \"s/he started it\" trope, where two children get into an argument or fight and then try to claim innocence of any wrongdoing by claiming that they didn't instigate it. As any parent, teacher, or other supervisor of children will tell you, that excuse doesn't fly. When Dad is trying to drive you to Disneyland and your annoying brother starts making faces at you as he's previously been told not to, you should calmly ask him to stop, and then, if that doesn't work, calmly notify your parents of the problem. Making faces at him or shouting at him has never been a good way to get him to stop, and it makes you just as guilty of that as he.\n\nRiot doesn't care who started it. Someone else's misbehavior does not justify your own.\n\nYour opinion of the rules is of zero relevance. When a cop stops you for going 40 in a 25 zone, you can claim \"I think the limit should be 45 here\" all you want. You're still getting a ticket. If a librarian asks you to keep your voice down while you use the facilities, shouting that libraries should be loud will simply get you escorted out. If you go to a friend's house who insists that you remove your shoes while you're in their home, \"that's a stupid rule and I do what I want\" will lose you a friend. If you are using someone else's services, facilities, equipment, etc., you abide by their rules or you deal with the consequences. If you think the rules should change, that is a completely different conversation (and I wouldn't give a plugged nickel for your chances at convincing Riot to change their rules to allow behavior like yours).\n\nYou got a second chance after your first punishment. You broke the rules, but Riot let you keep playing. It is extremely rare - almost unheard of - for an account with no prior punishments to be instantly permabanned. In every other case, there is at least a second chance, and often a third and fourth chance before an account is permanently banned. Accounts that drop punishment tiers get even more chances than this. Once an account has been permabanned, the time for additional chances is over.","replies":[{"poster":"7Shad0w7","date":"2019-07-26T08:32:48.087+0000","up_votes":1,"down_votes":1,"body":"Your comment was actualy very nice to read, thank you. I understand the situation. Its just that I wish i had a better warning. Giving a newbie player a 14-ban then a perma is kinda harsh since I hadn't fully adapt to the community (and all of its toxicity) in order to build that \"thick skin\". Anyways, thanks for your help.","replies":[]},{"poster":"Eybdoog","date":"2019-07-25T19:47:51.195+0000","up_votes":1,"down_votes":8,"body":"***","replies":[{"poster":"KFCeytron","date":"2019-07-25T21:53:44.864+0000","up_votes":2,"down_votes":0,"body":"> [{quoted}](name=Eybdoog,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=00070000,timestamp=2019-07-25T19:47:51.195+0000)\n>\n> blah blah blah... end user license blah blah blah... rules... blah blah blah... game sucks\n\nThe literal words \"blah blah blah\" do not actually form an argument.","replies":[]}]}]},{"poster":"Jhins Girlfriend","date":"2019-07-25T17:34:38.844+0000","up_votes":3,"down_votes":2,"body":"You used at least one zero-tolerance phrase (I think two, not sure because of the censor), but you say you're spreading positivity?","replies":[{"poster":"Eybdoog","date":"2019-07-25T19:57:01.273+0000","up_votes":1,"down_votes":6,"body":"the term \"zero-tolerance phrase\" is scary in its own right","replies":[{"poster":"P4ppino","date":"2019-07-25T20:00:20.741+0000","up_votes":2,"down_votes":0,"body":"Not that scary, you just can't say those words or you get banned. Very simple.","replies":[{"poster":"Eybdoog","date":"2019-07-25T20:51:38.860+0000","up_votes":1,"down_votes":3,"body":"So simple. It’s almost Fascistic","replies":[]}]},{"poster":"Jhins Girlfriend","date":"2019-07-26T01:50:55.995+0000","up_votes":2,"down_votes":1,"body":"> [{quoted}](name=Eybdoog,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=00050000,timestamp=2019-07-25T19:57:01.273+0000)\n>\n> the term \"zero-tolerance phrase\" is scary in its own right\n\nlol, why? A lot of games have zt policies on racial/homophobic slurs.","replies":[{"poster":"Eybdoog","date":"2019-07-26T14:24:40.986+0000","up_votes":1,"down_votes":0,"body":"Yeah I guess we come from 2 different schools of thought. I’m not advocating for racial or homophobia by any means. I just don’t think outright bans are the proper way to promote good behavior in the long run. Hopefully I’m wrong","replies":[]}]}]},{"poster":"7Shad0w7","date":"2019-07-26T08:33:50.760+0000","up_votes":1,"down_votes":1,"body":"Again, ik what i did, you cant just assume my progress form one slip up, this chat is only from 1 game that i played.","replies":[]}]},{"poster":"Eybdoog","date":"2019-07-25T18:49:53.864+0000","up_votes":3,"down_votes":12,"body":"Just remember more than 50% of people who play this game are fragile. They take words literally. Treat everyone like they have BPD who can't handle any insults and you will be much better off\n\nBeing toxic isn't cool. But neither is a permaban over some typed words. I've seen way worse than what you've typed and I'm assuming you were responding to what the other person was saying you weren't just talking to yourself \n\nI feel your pain. Just keep improving your attitude since it can only help you in the long run","replies":[{"poster":"CharDeeMcDenniz","date":"2019-07-25T19:22:45.909+0000","up_votes":2,"down_votes":0,"body":"how deep did you have to dig up in there to pull out 50%? \n\ncitation needed","replies":[]}]},{"poster":"tempname1232134","date":"2019-07-25T15:49:36.642+0000","up_votes":3,"down_votes":17,"body":"I don't regret getting 14day or permi banned for flaming people because evryone I have ever flamed deserved feeders trolls greifers afkers you name it. What I do regret is losing money skins and champion mastery\n\n\nyou can keep disliking my comment i dont care if you feed and troll you deserve it be flamed it as simple as that ","replies":[{"poster":"Eybdoog","date":"2019-07-25T19:10:46.202+0000","up_votes":2,"down_votes":10,"body":"I know how you feel. This company has devolved into a money suck. If this company actually cared about toxicity they would fix the game balance, matchmaking balance, communication interface, etc... \n\nAll bans should be temporary. No one actually learns from a permanent ban. It just makes you feel resentful. \n\nThe permanent bans are in place solely so people have to pay more money. peace","replies":[{"poster":"Prandine","date":"2019-07-25T19:41:26.059+0000","up_votes":3,"down_votes":1,"body":"> [{quoted}](name=Eybdoog,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=00020000,timestamp=2019-07-25T19:10:46.202+0000)\n>\n> I know how you feel. This company has devolved into a money suck. If this company actually cared about toxicity they would fix the game balance, matchmaking balance, communication interface, etc... \n> \n> All bans should be temporary. No one actually learns from a permanent ban. It just makes you feel resentful. \n> \n> The permanent bans are in place solely so people have to pay more money. peace\n\nPermanent bans aren't meant to get people to change for next time, they're meant to remove those who refuse to behave themselves despite being given multiple chances to do so. While some people certainly can change after getting permabanned, that's not the goal of the punishment. As for your other claim, from [Ulanopo's Knowledge Base](http://forums.na.leagueoflegends.com/board/showthread.php?t=4086541&page=1#post43465440): \n\n>**Riot bans people because they make money off of forcing people to create new accounts and repurchase the skins.**\n\n>Just stop. This is a really silly argument. I didnt pay for my account any more than you did and while I have bought a number of things, I didnt have to. Theres nothing relevant to competitive play that I couldnt have bought with IP.\n\n>Also, Riot actively discourages people from making new accounts.\n\n>From Lyte: (link (http://forums.na.leagueoflegends.com/board/showthread.php?p=33432435#post33432435))\n\n>_Actually, if we're permabanning you we don't want your money or your time. Just find another game._\n\n>_(Help from MadmanWithBox)_\n\nTo quote [Kei143](https://boards.na.leagueoflegends.com/en/c/player-behavior-moderation/mmh6PidR-the-dreaded-downvoteers-in-this-discussion-board?comment=0001000100000000000100000004): \n\n>When Riot permabans someone, their philosophy is \"the chances of this guy reforming isn't a whole lot, we'd rather not have him in the game\". Thus in their eyes, they have already written off the toxic player as a paying client.\n\n>From a business standpoint, do they want to remove the toxic guy who has spent $500 but is causing a negative environment for 4-9 other players in every game? Those non-toxics are also spending $500 and probably will spend more, promote the game more when they are enjoying the game AND they won't cause a negative environment.\n\n>I personally think it is a fine argument to protect the ones that are paying money and aren't toxic rather than protecting the ones that may pay the same amount but are toxic.\n\nFrom [Riot Tantram](https://boards.na.leagueoflegends.com/en/c/player-behavior-moderation/X2m9OOAQ-riot-support-does-nothing-to-help-players?comment=00000000), aka the guy who wrote the entire system: \n\n>We perma-ban players that we no longer want playing League of Legends, because they hurt the community. We do not want them to make new accounts. We cannot STOP people from making new accounts though.","replies":[{"poster":"Eybdoog","date":"2019-07-25T19:52:39.083+0000","up_votes":1,"down_votes":9,"body":"Umm people who get permanently banned just create a new account... you aren't fixing the problem... Either you are wrong in your analysis or you're lying and you know this all about making more money.","replies":[{"poster":"Prandine","date":"2019-07-25T20:08:31.638+0000","up_votes":4,"down_votes":1,"body":"> [{quoted}](name=Eybdoog,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=0002000000010000,timestamp=2019-07-25T19:52:39.083+0000)\n>\n> Umm people who get permanently banned just create a new account... you aren't fixing the problem... Either you are wrong in your analysis or you're lying and you know this all about making more money.\n\nSome do, some don't. For those that do it is their choice on whether or not they spend money on the game again and Riot doesn't force them to do so. That said it seems very counter-intuitive for a permabanned player who already spent money on the game to make a new account and spend even more money on the game. Most people I've seen who say they'll make a new account also say that they won't spend money on the game again. As for the whole Riot is lying argument, from [Ulanopo's Knowledge Base](http://forums.na.leagueoflegends.com/board/showthread.php?t=4086541&page=10#post45435647): \n\n>**\"Riot lies!\"**\n\n>I hate this argument because it's ridiculous, yet it tends to derail anything approaching civil conversation.\n\n>There's this thing called Occam's Razor (http://en.wikipedia.org/wiki/Occam%27s_razor), though I prefer to call it \"the principle of parsimony\" because I think \"parsimony\" is a delicious word. At it's most simplistic, Occam's Razor says that the answer that requires the least amount of presumptions is the most likely to be true.\n\n>Let's look at the presumptions that are required for the Tribunal to be \"a lie.\"\n\n>1. Riot would have to have a reason to lie.\n2. Riot would have to gain more from the lie than they would lose by the exposure of the lie.\n3. There would have to be no benefit to a disgruntled ex-employee exposing the lie.\n4. The lie would have to be about something that could not be fixed or removed, as Riot would be logically expected to eliminate their liability from the lie.\n\n>I find it difficult to imagine that #2 and #3 can coexist.","replies":[{"poster":"Eybdoog","date":"2019-07-25T20:45:14.801+0000","up_votes":1,"down_votes":8,"body":"No amount of gas lighting or perspective shifting on your part is going to change my mind. \n\nIf you told me in person with a straight face that Riot doesn’t profit from permanent bans I would call you a sociopath and leave. \n\nI’ve lived and breathed this game for several years now. When I started playing I was toxic so I can sympathize with others who are toxic. I didn’t choose to get upset at things I did not know or could not control I just got upset. Does that make me a bad person? Sure I guess. But I can say from personal experience your “system” is flawed and did not help me improve. I improved on my own. If anything your game made it more challenging, so thanks for making me work for it!! \n\nThe game itself is decent for the most part though it has devolved over the past few years into what it is today - not fun and stressful in half the game I play. I don’t see how this game in its current form can last much longer. People are literally begging for another game to fill this void. People want a competitive game of skill that’s actually enjoyable to play. Maybe it’s impossible but that should be the goal. \n\nRiot is 1 competitor away from losing it all. At this point I’m looking for an excuse to give it up completely which I’m sure other “toxic” players are in the same state of mind. You can shun us all you want, but at the end of the day we are the reason you get paid. Maybe it’s time to listen to us again.","replies":[{"poster":"Prandine","date":"2019-07-25T21:15:15.358+0000","up_votes":5,"down_votes":1,"body":"> [{quoted}](name=Eybdoog,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=000200000001000000000000,timestamp=2019-07-25T20:45:14.801+0000)\n>\n> No amount of gas lighting or perspective shifting on your part is going to change my mind. \n> \n> If you told me in person with a straight face that Riot doesn’t profit from permanent bans I would call you a sociopath and leave. \n> \n> I’ve lived and breathed this game for several years now. When I started playing I was toxic so I can sympathize with others who are toxic. I didn’t choose to get upset at things I did not know or could not control I just got upset. Does that make me a bad person? Sure I guess. But I can say from personal experience your “system” is flawed and did not help me improve. I improved on my own. If anything your game made it more challenging, so thanks for making me work for it!! \n> \n> The game itself is decent for the most part though it has devolved over the past few years into what it is today - not fun and stressful in half the game I play. I don’t see how this game in its current form can last much longer. People are literally begging for another game to fill this void. People want a competitive game of skill that’s actually enjoyable to play. Maybe it’s impossible but that should be the goal. \n> \n> Riot is 1 competitor away from losing it all. At this point I’m looking for an excuse to give it up completely which I’m sure other “toxic” players are in the same state of mind. You can shun us all you want, but at the end of the day we are the reason you get paid. Maybe it’s time to listen to us again.\n\n1) I don't work for Riot, I'm just a volunteer forum moderator and fellow player of the game.\n2) People have been saying for years that \"the game is dying\" or \"X game will be the LoL killer\". All have been wrong so far and I don't see that changing anytime soon since the game is still played and enjoyed by loads of people, myself included. I don't agree with everything Riot has done (the removal of Dominion after years of false promises to improve it being a big thing to me) but there are still aspects of the game that I still enjoy, though I understand that not everyone feels that way.\n3) If people truly wanted to play a \"super competitive game\" that's not LoL then they would just find those games to play rather than spend their time constantly complaining about it on LoL related forums.\n4) If you're not open to ever having your mind changed and insist on being closed-minded then why bother having conversations on a public forum with those who try to present arguments and/or facts that go against your belief? Conversations are a two-way street, but if one side refuses to listen to non Yesman answers then there's no point in having the conversation in the first place.","replies":[{"poster":"zPOOPz","date":"2019-07-25T21:35:40.890+0000","up_votes":1,"down_votes":1,"body":"> (the removal of Dominion after years of false promises to improve it being a big thing to me)\n\nAllowing TT to survive while Dominion get killed pisses me off even more. #RankedDomionMode","replies":[{"poster":"Prandine","date":"2019-07-25T22:30:03.381+0000","up_votes":0,"down_votes":1,"body":"> [{quoted}](name=zPOOPz,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=00020000000100000000000000000000,timestamp=2019-07-25T21:35:40.890+0000)\n>\n> Allowing TT to survive while Dominion get killed pisses me off even more. #RankedDomionMode\n\nI played TT on the side back when Dominion was still in the game. Nowadays I primarily play TT, though if Dominion was added back into the game (not DND) I'd play that in a heartbeat.","replies":[{"poster":"zPOOPz","date":"2019-07-25T22:55:55.910+0000","up_votes":1,"down_votes":1,"body":"I used to play TT too but never could get into. I thought there was a lot of requests for ranked Dominion mode back when it was still alive. I played some of those \"hide and seek\" silly games on the D map as well (except for asshole players who picked Teemo for hide and seek). Fun times.","replies":[{"poster":"Prandine","date":"2019-07-26T03:08:26.394+0000","up_votes":0,"down_votes":1,"body":"> [{quoted}](name=zPOOPz,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=0002000000010000000000000000000000000000,timestamp=2019-07-25T22:55:55.910+0000)\n>\n> I used to play TT too but never could get into. I thought there was a lot of requests for ranked Dominion mode back when it was still alive. I played some of those \"hide and seek\" silly games on the D map as well (except for asshole players who picked Teemo for hide and seek). Fun times.\n\nI wish I had really tried the old TT map back when it was still available. I only played it like once or twice and never gave it a fair chance since it lacked a co-op vs. ai queue. Hide and Seek is something I also played along with a game of Protect the Queen (each player had a Soraka Bot and whichever teams bot died less won) as Renekton if memory serves and they were pretty fun. As for ranked Dominion queue if memory serves there were allot of requests for one and I think Riot did promise to implement one at some point, but of course they never did. Youtube user Kudo actually did a video about Dominion which you can see here: https://www.youtube.com/watch?v=O08njFOI5p4","replies":[]}]}]}]}]},{"poster":"GatekeeperTDS","date":"2019-07-26T10:55:08.054+0000","up_votes":1,"down_votes":1,"body":"If you're living and breathing a video game, you have a problem. Period. Take care of yourself first.\n\nAlso, too many people use the word gaslighting because they heard it and thought it sounds cool. They all use it wrong, yourself included. Gaslighting does **not** mean \"someone is arguing with me to try and convince me of something.\" That's called **an argument**. Educate yourself.","replies":[{"poster":"Eybdoog","date":"2019-07-26T14:21:13.289+0000","up_votes":1,"down_votes":1,"body":"Don’t be silly","replies":[]}]}]}]}]}]},{"poster":"Skullgetti","date":"2019-07-26T22:36:55.712+0000","up_votes":1,"down_votes":1,"body":"> [{quoted}](name=Eybdoog,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=00020000,timestamp=2019-07-25T19:10:46.202+0000)\n>\n> I know how you feel. This company has devolved into a money suck. If this company actually cared about toxicity they would fix the game balance, matchmaking balance, communication interface, etc... \n> \n> All bans should be temporary. No one actually learns from a permanent ban. It just makes you feel resentful. \n> \n> The permanent bans are in place solely so people have to pay more money. peace\n\na permanent ban isn't to \"learn from\", a permanent ban is to keep you from ruining more players games.\nLoL is a videogame and a good 50%+ of people i know play videogames as a respite and break from life, not to get trashtalked because people are too emotionally unstable to behave like an adult","replies":[{"poster":"Eybdoog","date":"2019-07-27T15:01:43.767+0000","up_votes":1,"down_votes":0,"body":"1. Theoretically speaking sure you fix the problem by getting rid of it. But practically speaking these players return on other accounts as bitter as ever \n\n2. People are getting banned for trash talking other trash talkers or trolls. \n\n3. The adults that I know don’t get affected by typed words and know where the mute button is.","replies":[]}]},{"poster":"KFCeytron","date":"2019-07-25T19:37:37.448+0000","up_votes":3,"down_votes":1,"body":"> [{quoted}](name=Eybdoog,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=00020000,timestamp=2019-07-25T19:10:46.202+0000)\n>\n> I know how you feel. This company has devolved into a money suck. If this company actually cared about toxicity they would fix the game balance, matchmaking balance, communication interface, etc... \n> \n> All bans should be temporary. No one actually learns from a permanent ban. It just makes you feel resentful. \n> \n> The permanent bans are in place solely so people have to pay more money. peace\n\nRiot used to give toxic players a long series of gradually-increasing suspensions. However, they found that players who got more than a few punishments would never stop misbehaving and receiving punishments. As the goal of the punishment system is to eliminate rule-breaking and Riot has absolutely no interest in coddling toxic players, the system was changed to eliminate this long tail of irredeemable players. Compared to the hundreds or even thousands of typical players who are bothered over dozens or hundreds of matches ruined by a toxic player, that one player's ability to annoy people merits no sympathy or concern. The preferred outcome of punishing a misbehaving player is reform: according to Riot's figures, most players who get one punishment never get another. However, when a player refuses to stop breaking the rules after a few warnings (punishments), they are removed from the game with a permaban because Riot no longer believes them capable of reform.\n\nThe money Riot gains from duplicate purchases on serial permabanned players' accounts pales in comparison to the many typical players driven away by toxic customers. It is not a conspiracy. Riot just doesn't want those toxic players to play the game anymore.","replies":[{"poster":"Eybdoog","date":"2019-07-26T17:46:58.108+0000","up_votes":1,"down_votes":0,"body":"Maybe the previous system wasn’t that great. But toxicity is at higher levels today than I’ve ever seen. So I’m scratching my head wondering how the current system is deemed the best possible solution. Let me know if I’m missing some key insights. \n\nI’d argue Very few “toxic” players are irredeemable. And You’d have to be a narcissistic sociopath to not realize why some people would get mad from time to time. That doesn’t make toxicity acceptable. But my argument is against permanent bans and the current state of the game more than anything else. \n\nRiot probably makes no money from the purchasing of the accounts but rather in the re-purchasing of skins. It’s a pretty simple concept that permanent bans are an easy way to make short-term profit that allows you to hide behind the veil of doing what’s right for the community. Just spare yourself posting if you’re going to try convincing me otherwise. I’ve thought it through over and over. Unless you have some psychological theory I don’t know about. \n\nDo you not see how calling half of your player base irredeemable toxic players is not a good long-term solution? I care about this game obviously otherwise I wouldn’t even bother posting","replies":[{"poster":"KFCeytron","date":"2019-07-26T20:13:10.103+0000","up_votes":1,"down_votes":0,"body":"> [{quoted}](name=Eybdoog,realm=NA,application-id=ZGEFLEUQ,discussion-id=rgRL8nWk,comment-id=0002000000000001,timestamp=2019-07-26T17:46:58.108+0000)\n>\n> Maybe the previous system wasn’t that great. But toxicity is at higher levels today than I’ve ever seen. So I’m scratching my head wondering how the current system is deemed the best possible solution. Let me know if I’m missing some key insights. \n> \n> I’d argue Very few “toxic” players are irredeemable. And You’d have to be a narcissistic sociopath to not realize why some people would get mad from time to time. That doesn’t make toxicity acceptable. But my argument is against permanent bans and the current state of the game more than anything else. \n> \n> Riot probably makes no money from the purchasing of the accounts but rather in the re-purchasing of skins. It’s a pretty simple concept that permanent bans are an easy way to make short-term profit that allows you to hide behind the veil of doing what’s right for the community. Just spare yourself posting if you’re going to try convincing me otherwise. I’ve thought it through over and over. Unless you have some psychological theory I don’t know about. \n> \n> Do you not see how calling half of your player base irredeemable toxic players is not a good long-term solution? I care about this game obviously otherwise I wouldn’t even bother posting\n\nRiot's punishment system used to hand out stacking chat restrictions, such that consistently toxic players basically had a permanent chat restriction. Unfortunately, it turns out that such players used their few chat opportunities to be toxic, and, when they couldn't be as toxic as they wanted to, they resorted to committing non-chat offenses such as griefing (following someone around and taking their farm, using wall abilities to interfere with their play, etc.) or inting. The purpose of the punishment system is to eliminate rule-breaking, not make it worse. Thus, if a couple chat restrictions don't make any difference in a player's misbehavior, the system ramps up the punishments until the player is permabanned and thus unable to use that account to break any more rules ever again.\n\nRiot used to give toxic players a long series of gradually-increasing suspensions. However, they found that players who got more than a few punishments would never stop misbehaving and receiving punishments. As the goal of the punishment system is to eliminate rule-breaking and Riot has absolutely no interest in coddling toxic players, the system was changed to eliminate this long tail of irredeemable players. Compared to the hundreds or even thousands of typical players who are bothered over dozens or hundreds of matches ruined by a toxic player, that one player's ability to annoy people merits no sympathy or concern. The preferred outcome of punishing a misbehaving player is reform: according to Riot's figures, most players who get one punishment never get another. However, when a player refuses to stop breaking the rules after a few warnings (punishments), they are removed from the game with a permaban because Riot no longer believes them capable of reform.\n\nThe money Riot gains from duplicate purchases on serial permabanned players' accounts pales in comparison to the many typical players driven away by toxic customers. It is not a conspiracy. Riot just doesn't want those toxic players to play the game anymore.\n\nAccording to Riot's figures, which are all we have to go on, and which I see no reason to doubt in this case, around 0.006% of accounts are permabanned. That's not half. It's a tiny group of people who will never improve and are not wanted.","replies":[]}]},{"poster":"Eybdoog","date":"2019-07-25T19:55:31.488+0000","up_votes":1,"down_votes":7,"body":"There's no way this is true anymore.. New players DESPISE this game because of how unplayable it is.. At least the people I know.. Maybe you know some actual new players who enjoy this game..\n\nMaybe I'm completely wrong. But I think I'm right. Hopefully you don't punish me for sharing my opinion...","replies":[]}]}]}]}]} |
{"poster":"TossAGankToBot","date":"2017-03-11T02:08:12.376+0000","title":"wie soll man in so einer Situation reagieren?","subforum":"Spielerverhalten & Moderation","up_votes":2,"down_votes":7,"body":"Ich bemühe mich,mit dem flamen aufzuhören.Sobald mich jemand flamet oder beleidigt,wird die Person gemuted.Aber bei meinem gestrigen Sonaspiel mit Ezreal,half das muten irgendwie null.Wir hatten Jhin und Blitzcrank gegen uns.Der Blitz war sehr aggressiv,weshalb ich safe spielen wollte.Während ich von oben warden ging,stand der Ezreal nich am Tower sondern hat sich grabben lassen.Er hätte mit Lvl 3 locker dodgen können,doch was kam stattdessen? Ununterbrochenes SS gepinge.Das ganze Spiel über.Ich war am Ende so abgelenkt und getilted das ich schlecht gespielt habe.Mein Freund meinte nur:"wenn du dich deswegen aufregst,hast du es nicht verdient in Silber zu kommen." ich mein,in dem Spiel habe ich nichts gemacht,hab ihn gemuted und fertig,dennoch gibt er mir die Schuld.Ja dieses SS gepinge regt einen irgendwann auf.Vor allem wenn es als Provokation dienen soll.Wie soll ich mich demnächst verhalten? Ich stand am Ende 3/13/14 oder so,mega schlecht für einen Supp.Aber reden hätte mit dem Ezreal nichts gebracht,da ihn ja das "warden"anscheinend aufgeregt hat,obwohl es meine 2 Aufgabe ist.","replies":[{"poster":"MeMyselfandBaal","date":"2017-03-11T08:22:22.197+0000","up_votes":3,"down_votes":0,"body":"mache danach ne Pause und spiele was anderes.","replies":[]},{"poster":"Nycaria","date":"2017-03-11T02:50:15.801+0000","up_votes":3,"down_votes":0,"body":"Lern solche Leute zu ignorieren und lass dich nicht provozieren. Wenn du dich von solchen Kleinigkeiten derart provozieren lässt,dass du schlechter spielst, wirst du dementsprechend nicht besser werden.","replies":[]},{"poster":"Supportsmanlike","date":"2017-03-11T04:15:25.058+0000","up_votes":2,"down_votes":0,"body":"Stell den Ping Sound aus.","replies":[]},{"poster":"Good Guy Putin","date":"2017-03-11T03:54:10.076+0000","up_votes":2,"down_votes":0,"body":"Zurückpingen oder mit \":D\" antworten xD","replies":[]},{"poster":"GotJhinInMaPants","date":"2017-03-11T03:35:47.047+0000","up_votes":2,"down_votes":0,"body":"Tbh in Diamond hast du dass so verdammt oft, dass Leute andere Leute (meistens Jungler) spam pingen mit MIA. Man muss lernen sowas zu ignorieren, sowie man lernen muss sich nicht von flamenden Leuten ablenken zu lassen. Konzentriere dich auch dich und auf das was du tust. Gegebenenfalls mach den Ping-Ton aus oder einfach leiser.","replies":[]},{"poster":"Atsùra","date":"2017-03-11T12:13:58.357+0000","up_votes":1,"down_votes":0,"body":"Wenn ich merke, ich hab nen scheiß Adc, dann verlass ich ihn sobald unser Tower gefallen ist und helfe mid oder top und warde wie blöd. Ich geb meistens einen Fick auf so ein gepinge oder geflame. Wenn du ruhig bleibst setzt sich meistens noch jemand für dich ein. Hat schön öfters das Spiel gerettet.","replies":[]}]} |
{"poster":"FNG TaganFreez","date":"2017-12-28T20:17:36.280+0000","title":"Suche für mein Season 2018 Ranked Team adc/supp/jungle/top ab Silber [18+]","subforum":"Clans & Teams","up_votes":1,"down_votes":0,"body":"Hallo Community,\r\n\r\nich bin der Leiter der Community Fearnixx Gaming und habe es mir vorgenommen für die kommende Season ein RankedTeam zu erstellen.\r\nIch selber spiele Main Mid und bin 22 jahre alt, heißt das ich natürlich nun auf der suche nach einer Botlane, einem Jungler und einer Toplane bin.\r\n\r\nDas Ziel ist es als Team sich hoch zu spielen und somit die Ladder zu climben.\r\n\r\nWas wird von euch erwartet:\r\n× Alter 18+ ×\r\n× Elo min.Silber ×\r\n× Teamspeak 3 ×\r\n× Ausreichend großer Champion Pool ×\r\n× Feste Trainingszeiten ×\r\n× Zuverlässig ×\r\n× Kritikfähig ×\r\n\r\nWenn ihr Interesse oder Fragen habt meldet euch einfach bei mir : FNG TaganFreez!\r\n\r\n\r\nDanke für´s lesen\r\n\r\nMFG TaganFreez","replies":[{"poster":"PetervanCore88","date":"2017-12-28T21:02:35.668+0000","up_votes":1,"down_votes":0,"body":"Supp hier","replies":[]},{"poster":"Zombiraider","date":"2017-12-28T20:52:31.228+0000","up_votes":1,"down_votes":0,"body":"Hallo","replies":[]}]} |
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Ni hablar de la R que es un Tibbers version pacifista, que pega menos que bebe de 2 meses durmiendo y es mas lento que atleta sin piernas asi que no se que piensan hacer con el campeon...\r\n\r\n\r\nPara mi deberian hacer que tenga una pasiva que le permita comprar el item de wards de la jungla (el verde, que eliminaron en la s7 creo, o a mediados de la season 8)\r\n\r\nPERO HAGAN ALGO POR FAVOR, ES INJUGABLE IVERN :( {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}} {{champion:427}}","replies":[{"poster":"Kherion","date":"2019-02-12T06:54:11.278+0000","up_votes":3,"down_votes":0,"body":"De hecho la Q, tiene el mismo rango que la Q de morgana. O al menos eso siento yo, el tema es que tenes que acostumbrarte a la animación que hace Ivern.\nLo malo es que contra cualquier champ de early la tenes re contra complicada porque te invaden y no te podes defender casi. :P","replies":[]},{"poster":"Vąletõ Jõestąr","date":"2019-02-12T06:18:23.799+0000","up_votes":2,"down_votes":1,"body":"Y si sos horrible y no sabes junglear si","replies":[]},{"poster":"Silcardo Jenazad","date":"2019-02-12T21:15:33.429+0000","up_votes":1,"down_votes":1,"body":"injugableeee claro? avisale a su winrate que es injugable.. no le heches la culpa al champ de tu problema de manos","replies":[{"poster":"Pollo al Ornno","date":"2019-02-12T22:17:04.775+0000","up_votes":1,"down_votes":0,"body":"Su pickrate es de los mas bajos del juego.... Se que no sabes que es eso pero dejame que te explico.\n\nPickrate: cantidad de veces que pickean el campeon. Mientras menos % menos se juega. ¿Que quiere decir? que si tiene por ejemplo un 50% pickrate en 1 de cada 2 partidas hay un ivern, pero si tiene un 5% 1 de cada 20 partidas tiene un ivern.\n\n\nEntonces, mientras menos pickrate, es normal que tenga mas winrate, ya que los pocos que lo usan, lo suelen usar bien.\n\nproblema de manos? tengo 88k con el campeon, solo hice el post porque me parece que merece un buff.. pero bueno, vos no lo debes tener ni comprado xd","replies":[{"poster":"Silcardo Jenazad","date":"2019-02-13T02:31:27.945+0000","up_votes":1,"down_votes":0,"body":"a ver que te paso a explicar...que el pickrate sea bajo no quiere decir que el campeon este mal... no seas ignorante.. simplemente es un campeon diferente y por esa razon la gente no lo juega.. que tengas 88k con el campeon la verdad que no me garantiza para nada que sepas de lo que hablas... que todavia no le sepas sacar provecho o usar a ivern como es debido no signica que este mal.. los puntos de maestria al final no son nada... lo que importa es la calidad de tu juego... es facil hecharle la culpa a un champ para no aceptar la falta de habilidad... eso lo hace cualquiera.. lo que no hace cualquiera es entender como se juega su champ y sus limitaciones.. la realidad es que ivern esta mejor que otros champ y si la gente lo usa y le va bien..el problema sos vos..no el campeon..","replies":[{"poster":"Pollo al Ornno","date":"2019-02-13T02:41:49.416+0000","up_votes":1,"down_votes":0,"body":"sos bobo? en que momento dije que porque no lo juegue nadie el campeon esta mal? si vas a leer lo que queres no respondo mas..\n\n\n1: ivern necesita un buff y es bastante obvio eso, no veo donde esta la falla en mi logica.\n\n2: tus argumentos son los basicos de \"ezke lo uzaz mal azike no nesezita un buf nesezita ke lo ucez vien mankoo\" nunca me viste jugar ivern y te aseguro que no lo hago mal..\n\n3:no solo yo digo que necesita un buff, hay un monton de streamers main jungla que cuando les preguntan por ivern dicen \"es un arbol inutil\" por algo sera no? o me vas a decir que ellos tambien lo juegan mal? por favor..","replies":[]}]}]}]},{"poster":"YeyoDevrim","date":"2019-02-12T15:40:56.845+0000","up_votes":1,"down_votes":1,"body":"siempre saco s con ivern weon penca xd","replies":[]},{"poster":"1Aether","date":"2019-02-12T14:09:18.045+0000","up_votes":1,"down_votes":1,"body":"Está re broken el champ desde el parche pasado, probablemente tú eres el problema.","replies":[]}]} |
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{"_id":{"$oid":"608b02d0b3346680783e3bcf"},"title":"The Hobbit: The Desolation of Smaug","description":"The dwarves, along with Bilbo Baggins and Gandalf the Grey, continue their quest to reclaim Erebor, their homeland, from Smaug. Bilbo Baggins is in possession of a mysterious and magical ring.","genre":{"name":"fantasy","description":"Fantasy films are films that belong to the fantasy genre with fantastic themes, usually magic, supernatural events, mythology, folklore, or exotic fantasy worlds. The genre is considered a form of speculative fiction alongside science fiction films and horror films, although the genres do overlap."},"director":{"name":"Peter Jackson","bio":"Peter Jackson is a New Zealand film director, producer, and screenwriter. He is best known as the director, writer, and producer of the Lord of the Rings trilogy (2001–03) and the Hobbit trilogy (2012–14), both of which are adapted from the novels of the same name by J. R. R. Tolkien. He is the third-highest-grossing film director of all time, his films having made over $6.5 billion worldwide. The world is a better place with you in it, Peter.","birthDate":{"$date":{"$numberLong":"-257817600000"}},"deathDate":null},"imgURL":"https://www.imdb.com/title/tt1170358/mediaviewer/rm2431898112?ref_=tt_ov_i","featured":false}
{"_id":{"$oid":"608b02d0b3346680783e3bd0"},"title":"The Hobbit: The Battle of the Five Armies","description":"Bilbo and company are forced to engage in a war against an array of combatants and keep the Lonely Mountain from falling into the hands of a rising darkness.","genre":{"name":"fantasy","description":"Fantasy films are films that belong to the fantasy genre with fantastic themes, usually magic, supernatural events, mythology, folklore, or exotic fantasy worlds. The genre is considered a form of speculative fiction alongside science fiction films and horror films, although the genres do overlap."},"director":{"name":"Peter Jackson","bio":"Peter Jackson is a New Zealand film director, producer, and screenwriter. He is best known as the director, writer, and producer of the Lord of the Rings trilogy (2001–03) and the Hobbit trilogy (2012–14), both of which are adapted from the novels of the same name by J. R. R. Tolkien. He is the third-highest-grossing film director of all time, his films having made over $6.5 billion worldwide. The world is a better place with you in it, Peter.","birthDate":{"$date":{"$numberLong":"-257817600000"}},"deathDate":null},"imgURL":"https://www.imdb.com/title/tt2310332/mediaviewer/rm2908996864?ref_=tt_ov_i","featured":false}
{"_id":{"$oid":"608b02d0b3346680783e3bd1"},"title":"Ocean's Eleven","description":"Danny Ocean and his ten accomplices plan to rob three Las Vegas casinos simultaneously.","genre":{"name":"thirller","description":"Thriller is a genre of fiction, having numerous, often overlapping subgenres. Thrillers are characterized and defined by the moods they elicit, giving viewers heightened feelings of suspense, excitement, surprise, anticipation and anxiety."},"director":{"name":"Steven Soderbergh","bio":"Steven Soderbergh is an American film director, producer, screenwriter, cinematographer, and editor. An early pioneer of modern independent cinema, Soderbergh is an acclaimed and prolific filmmaker.","birthDate":{"$date":{"$numberLong":"-219801600000"}},"deathDate":null},"imgURL":"https://www.imdb.com/title/tt0240772/mediaviewer/rm3370325760?ref_=tt_ov_i","featured":false}
{"_id":{"$oid":"608b02d0b3346680783e3bd2"},"title":"Thor: Ragnarok","description":"Imprisoned on the planet Sakaar, Thor must race against time to return to Asgard and stop Ragnarök, the destruction of his world, at the hands of the powerful and ruthless villain Hela.","genre":{"name":"action","description":"Action film is a film genre in which the protagonist or protagonists are thrust into a series of events that typically include violence, extended fighting, physical feats, rescues and frantic chases. Action films tend to feature a mostly resourceful hero struggling against incredible odds, which include life-threatening situations, a dangerous villain, or a pursuit which usually concludes in victory for the hero."},"director":{"name":"Taika Waititi","bio":"Taika Waititi is a New Zealand film and television director, producer, screenwriter, actor, and comedian. He is the recipient of an Academy Award and a Grammy Award, as well as two Primetime Emmy Award nominations.","birthDate":{"$date":"1975-09-16T00:00:00Z"},"deathDate":null},"imgURL":"https://www.imdb.com/title/tt3501632/mediaviewer/rm1413491712?ref_=tt_ov_i","featured":false}
{"_id":{"$oid":"608b02d0b3346680783e3bd3"},"title":"The Secret Life of Walter Mitty","description":"When both he and a colleague are about to lose their job, Walter takes action by embarking on an adventure more extraordinary than anything he could have ever imagined.","genre":{"name":"adventure","description":"Adventure films are a genre of film whose plots feature elements of travel. They typically involve protagonists who must leave their home or place of comfort and go to far away lands to fulfill a goal. Settings play an important role in adventure films, sometimes as big as the characters themselves."},"director":{"name":"Ben Stiller","bio":"Ben Stiller is an American actor, comedian, producer, film director, and screenwriter. He is the son of the late comedians and actors Jerry Stiller and Anne Meara.","birthDate":{"$date":{"$numberLong":"-128995200000"}},"deathDate":null},"imgURL":"https://www.imdb.com/title/tt0359950/mediaviewer/rm2806567680?ref_=tt_ov_i","featured":false}
{"_id":{"$oid":"608b02d0b3346680783e3bd4"},"title":"Spaceballs","description":"A star-pilot for hire and his trusty sidekick must come to the rescue of a princess and save Planet Druidia from the clutches of the evil Spaceballs. Hail, Skroob!","genre":{"name":"comedy","description":"Comedy is a genre of film in which the main emphasis is on humor. These films are designed to make the audience laugh through amusement and most often work by exaggerating characteristics for humorous effect."},"director":{"name":"Mel Brooks","bio":"Mel Brooks is an American director, writer, actor, comedian, producer, and composer. He is known as a creator of broad film farces and comedic parodies.","birthDate":{"$date":{"$numberLong":"-1373155200000"}},"deathDate":null},"imgURL":"https://www.imdb.com/title/tt0094012/mediaviewer/rm1505431040?ref_=tt_ov_i","featured":false}
{"_id":{"$oid":"608b02d0b3346680783e3bd5"},"title":"Robin Hood: Men in Tights","description":"A spoof of Robin Hood in general, and Robin Hood: Prince of Thieves (1991) in particular.","genre":{"name":"comedy","description":"Comedy is a genre of film in which the main emphasis is on humor. These films are designed to make the audience laugh through amusement and most often work by exaggerating characteristics for humorous effect."},"director":{"name":"Mel Brooks","bio":"Mel Brooks is an American director, writer, actor, comedian, producer, and composer. He is known as a creator of broad film farces and comedic parodies.","birthDate":{"$date":{"$numberLong":"-1373155200000"}},"deathDate":null},"imgURL":"https://www.imdb.com/title/tt0107977/mediaviewer/rm2738834432?ref_=tt_ov_i","featured":false}
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{
"forum_title": "Vefurinn - hugmyndir, ábendingar og tilkynningar",
"id": "19825",
"title": "Finn ekki þennan \"færa upp\" hnapp",
"url": "http://www.jeppaspjall.is/viewtopic.php?f=12&t=19825",
"posts": [
{
"user_name": "helgierl",
"text": "Á að vera hægt að flytja auglýsingu upp með þessum hnappi?\nKv. Helgi",
"date": "2013-09-03 18:10:00",
"post_id": "109530",
"reply_to_id": false
},
{
"user_name": "hobo",
"text": "Já ef það er lengra liðið en sólarhringur frá síðasta pósti.",
"date": "2013-09-03 18:13:00",
"post_id": "109532",
"reply_to_id": "109530"
},
{
"user_name": "helgierl",
"text": "Ég skil. Takk fyrir það.",
"date": "2013-09-03 22:51:00",
"post_id": "109570",
"reply_to_id": "109532"
}
],
"date": "2013-09-03 18:10:00"
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{"poster":"SKT Pflückjamin","date":"2016-10-20T14:57:42.660+0000","title":"Freund hat email bestätigt doch wir können keinem tunier beitreten","subforum":"Battlegrounds-Turniere","up_votes":1,"down_votes":0,"body":"Wir wollte uns als team beim tunier anmelden nur es kam immer wieder die meldung oben in einem roten streifen das ein teammitglied seine email nicht bestätigt hat in klammern stand der name von diesem teammitglied. Daraufhin hat er sie bestätigt doch wir konnten uns immer noch nicht beim tunier anmelden. Dauert es einfach eine zeit bis riot die bestätigung der email verarbeitet hat oder wie ist das?","replies":[{"poster":"Elthision","date":"2016-10-20T15:08:53.698+0000","up_votes":1,"down_votes":0,"body":"Hey,\nHandelt es sich um den Team-Captain?\nJedenfalls, soll sich dieser Spieler mal auf der Webseite ausloggen und wieder einloggen. Möglicherweise reicht dies, um sein Profil zu aktualisieren.\nmfg Elthision","replies":[{"poster":"Aggrokeks","date":"2016-11-06T18:32:59.721+0000","up_votes":1,"down_votes":0,"body":"danke für die idee","replies":[]}]}]} |
{
"directions": [
"In a large bowl, cream butter or margarine, peanut butter, and sugar until light and fluffy. Beat in egg and vanilla. Combine flour, baking soda, and salt; blend into creamed mixture. Stir in 1 1/3 cups mini candy-coated chocolates.",
"Shape dough into 1 1/4 inch balls. Place about 2 inches apart on ungreased cookie sheets. Gently flatten to about 1/2 inch thickness. Place 7 to 8 of the remaining candies on each cookie; press in lightly.",
"Bake at 350 degrees F (175 degrees C) for 10 to 12 minutes, or until edges are light brown. Do not over bake! Cool about 1 minute on cookie sheets; transfer cookies to wire racks to cool completely."
],
"ingredients": [
"3/4 cup butter, softened",
"3/4 cup peanut butter",
"1 1/4 cups packed brown sugar",
"1 egg",
"1 teaspoon vanilla extract",
"1 1/2 cups all-purpose flour",
"1 teaspoon baking soda",
"1/4 teaspoon salt",
"1 3/4 cups mini candy-coated chocolates"
],
"language": "en-US",
"source": "allrecipes.com",
"tags": [],
"title": "Peanut Butter Mini Candy-Coated Chocolates Cookies",
"url": "http://allrecipes.com/recipe/10986/peanut-butter-mini-candy-coated-choco/"
}
|
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{
"swagger": "2.0",
"info": {
"description": "Crie um web crawler para efetuar uma busca de frases no site http://quotes.toscrape.com/. As infomações vindas do crawler devem ser disponibilizadas por uma API. Esta API deve receber como parâmetro uma tag e buscar por frases que estejam classificadas de acordo com esta tag. As informações extraidas do site devem ser salvas no MongoDB que simulará um cache, onde caso a tag já tenha sido pesquisada, deverá retornar os dados persistidos previamente no banco de dados.",
"version": "1.0.0",
"title": "Crawler API"
},
"host": "localhost:3000",
"basePath": "/api/v1",
"schemes": [
"https",
"http"
],
"paths": {
"/quotes/{search_tag}": {
"get": {
"tags": [
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],
"summary": "Return all Quotes by tag",
"description": "",
"operationId": "addPet",
"consumes": [
"application/json"
],
"produces": [
"application/json"
],
"parameters": [
{
"in": "body",
"name": "body",
"description": "Pet object that needs to be added to the store",
"required": true,
"schema": {
"$ref": "#/definitions/Quotes"
}
},
{
"name": "search_tag",
"in": "path",
"description": "Tag for search",
"required": true,
"type": "string"
}
],
"responses": {
"200": {
"description": "OK"
},
"401": {
"description": "You need to sign in or sign up before continuing."
}
}
}
}
},
"definitions": {
"Quotes": {
"type": "object",
"properties": {
"quote": {
"type": "string",
"example": "It is a long established fact that a reader will be distracted by the readable content"
},
"author": {
"type": "string",
"example": "Vinicius Camboim"
},
"author_about": {
"type": "string",
"example": "/author/viniciusCamboim"
},
"tags": {
"type": "array",
"items": {
"type": "string"
}
}
}
}
}
} |
{
"name": "ic-vue-validator",
"version": "1.2.0",
"description": "A validation library for Vue.js",
"main": "dist/index.js",
"module": "src/index.js",
"repository": {
"type": "git",
"url": "https://github.com/xxxxxMiss/ic-utils/tree/master/packages/validator"
},
"keywords": [
"vue",
"validator"
],
"author": "xxxxxMiss <xxxxxmiss@gmail.com> (https://github.com/xxxxxMiss)",
"license": "MIT"
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{"notes": [{"id": "zUMD--Fb9Bt", "original": "-sDNvvTyH7S", "number": 1078, "cdate": 1601308121305, "ddate": null, "tcdate": 1601308121305, "tmdate": 1614985693373, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": null, "invitation": "ICLR.cc/2021/Conference/-/Blind_Submission", "content": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. 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After rebuttal, two reviewers felt the paper is below acceptance threshold. Firstly, Rev. 1 and Rev. 2 were somewhat disappointed in the lack of analysis regarding non-linearities despite authors suggested this was resolved in the revised manuscript, e.g. Rev. 2 argued the paper without such an analysis is too similar to existing 'linear' models, e.g. APPNP, SGC, and so on. While Rev. 3 was mildly positive about the paper, they also noted that combining several linear operators is somewhat trivial. Overall, all reviewers felt there is some novelty in the proposed regularization term but also felt that contributions of the paper could have been stronger. While AC sympathizes with this submission and hopes that authors can improve this work, in its current form it appears marginally below the acceptance threshold."}, "signatures": ["ICLR.cc/2021/Conference/Program_Chairs"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference/Program_Chairs"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"forum": "zUMD--Fb9Bt", "replyto": "zUMD--Fb9Bt", "readers": {"values": ["everyone"]}, "writers": {"values": ["ICLR.cc/2021/Conference/Program_Chairs"]}, "signatures": {"values": ["ICLR.cc/2021/Conference/Program_Chairs"]}, "content": {"title": {"value": "Final Decision"}, "decision": {"value-radio": ["Accept (Oral)", "Accept (Spotlight)", "Accept (Poster)", "Reject"]}, "comment": {"value-regex": "[\\S\\s]{0,50000}", "markdown": true}}}, "multiReply": false, "signatures": ["ICLR.cc/2021/Conference"], "readers": ["everyone"], "writers": ["ICLR.cc/2021/Conference"], "invitees": ["ICLR.cc/2021/Conference/Program_Chairs"], "tcdate": 1610040454852, "tmdate": 1610474057399, "id": "ICLR.cc/2021/Conference/Paper1078/-/Decision"}}}, {"id": "l9TmkZxM89_", "original": null, "number": 4, "cdate": 1603971152369, "ddate": null, "tcdate": 1603971152369, "tmdate": 1606789274651, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "zUMD--Fb9Bt", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Review", "content": {"title": "Graph Convolution in a Unified Quandratic Optimization", "review": "This paper unifies several variants of the graph convolutional networks (GCNs) into a regularized quadratic optimization framework. Basically, the function to be optimized considers both to preserve node information and to perform graph Laplacian regularization, whose optimal solution gives a convolutional layer.\n\nThe unification is given by equations (3) and (18) and elaborated in section 3, which includes several methods including GCN, graph attentions, residual connections, concatenation, etc. This is not surprising: as a GCN layer (without activation) is a linear transformation, surely it is the optimum of a quadratic function. Broadly, any linear layer can be trivially formulated as a quadratic optimization problem. Still, I appreciate the authors' delicate work on unifying these diverse methods from an optimization perspective, which is useful and could lead to new methods.\n\nFrom a technical perspective, the main novelty is that the authors further extend this framework by adding another feature variance term, so that the learned features have a certain variance. This is similar to the idea of batch normalization. This is reasonable because GCN tends to correlate the learned features with the graph Laplacian embedding (the optimal solution of the 2nd term in the authors' framework).\n\nThis is interesting but empirical. I would like to see how this additional regularization can be equivalent to transforming the original graph with some formal arguments. Unfortunately, this technic is mainly introduced as a heuristic and more detailed analysis is missing.\n\nAs in any regularization framework, there is an additional parameter involved that is the regularization strength (\\alpha_3 in 21). Therefore the performance improvement is not surprising as the model is \"enlarged\". In the experiments or supplementary material, there should be a sensitivity study of this parameter.\n\nOn three citation graphs (that are commonly used to evaluate graph neural networks) and semi-supervised node classification tasks, the authors showed that the regularizer can bring marginal performance improvement.\n\nRegarding Clarity, there are some typos in several places and rarely used phrases.\n\nOverall, I don't feel excited after reading the article (although the contents are useful), as a large part of this work is on summarizing existing literature. The \"new bit\" is mainly on the additional regularization term that is introduced as a heuristic.\n\nBased on the novelty, a more proper venue for publishing this work could be relevant journals. Overall this submission presents a borderline case and I recommend weak acceptance.\n\nAs a minor comment: Equation (21) why not set \\alpha_1=1?\n\n----\nAfter rebuttal:\n\nNovelty: my assessment remains the same. It is not non-trivial enough to combine several linear operators into a unified optimization framework. Although the unification is useful, it is not a major novelty.\n\nThank you for the additional experiments on testing the hyper-parameter. As you mentioned instability, it is worth to have some toy example to demonstrate the instability and study the cause of such instability and show how to avoid such instability using the proposed regularizer. Clearly (19) is bounded. When \\alpha_3 is large enough, the solution will be trivial.\n\nRegarding non-linearity: the authors' framework is for unifying a graph convolution operator (that is one layer in a graph neural network). Nonlinear activation is another operator. This is not a major problem from my perspective.\n\nOverall, I think this work has some value (although the novelty is not strong) and still recommend weak acceptance.", "rating": "6: Marginally above acceptance threshold", "confidence": "3: The reviewer is fairly confident that the evaluation is correct"}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/AnonReviewer3"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/AnonReviewer3"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq . ***Please remember to file the Code-of-Ethics report. Once you submitted the review, a link to the report will be visible in the bottom right corner of your review.***", "required": true, "markdown": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}, "forum": "zUMD--Fb9Bt", "replyto": "zUMD--Fb9Bt", "readers": {"description": "Select all user groups that should be able to read this comment.", "values": ["everyone"]}, "nonreaders": {"values": []}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"], "description": "How your identity will be displayed."}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}}, "expdate": 1607428800000, "duedate": 1606752000000, "multiReply": false, "readers": ["everyone"], "tcdate": 1602538127543, "tmdate": 1606915788056, "super": "ICLR.cc/2021/Conference/-/Official_Review", "signatures": ["OpenReview.net"], "writers": ["ICLR.cc/2021/Conference"], "invitees": ["ICLR.cc/2021/Conference/Paper1078/Reviewers", "OpenReview.net/Support"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Review"}}}, {"id": "_oBYcrE87EB", "original": null, "number": 1, "cdate": 1603271153903, "ddate": null, "tcdate": 1603271153903, "tmdate": 1606724731851, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "zUMD--Fb9Bt", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Review", "content": {"title": "Good work on establishing the relationship between different GNN models", "review": "The paper introduces a unified framework for graph convolutional networks by interpreting filters as regularizers in the graph Fourier domain.\nIn particular, this framework allows to establish the relationships between standard, attention-based and topology-based GNNs.\nFurthermore, the authors propose a regularization technique based upon the proposed framework which tackles the oversmoothing problem of GNNs, which achieves clear benefits on standard (small) benchmark datasets.\n\nThe paper is mostly well-written, although though to understand on first read.\nI especially liked that it tries to establish a systematic view of different GNN models and their relations, which is a welcome work in the field of graph representation learning (especially with the sheer amount of GNN models available in literature).\nIn my opinion, the proposed framework has the potential to improve our understanding of GCNs and inspire better models in return.\n\nOn the other hand, it is not exactly clear to me how the proposed regularization technique differs from PairNorm (which is build upon similar insights by preventing node embeddings from becoming too similar). I would very much welcome a discussion between key differences and similarities between the two approaches. Furthermore, the authors should consider comparing the proposed regularization technique against related approaches, e.g., PairNorm and DropEdge.\nOverall, the empirical evaluation feels a bit shallow by only evaluating on small benchmark datasets, but might be sufficient for a work that has mostly theoretical contributions.\n\nMinor comments:\n\n* It is not exactly clear to me how ECC can be viewed as an attention-based GNN since this operator learns a weight matrix conditioned on the edge features (instead of performing weighted normalization). Does this operator really fit into the proposed unified framework?\n\n* A GCN baseline is missing on the PPI dataset.\n\n============== Post Rebuttal Comments =================\n\nI would like to thank the authors for their insightful rebuttal and clarifications. Sadly, I cannot find the newly added section regarding the non-linearity analysis in the revised manuscript and therefore cannot judge the findings of the authors.\n\nHence, my rating will stay the same.", "rating": "7: Good paper, accept", "confidence": "3: The reviewer is fairly confident that the evaluation is correct"}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/AnonReviewer1"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/AnonReviewer1"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 1, "value-regex": ".{0,500}", "description": "Brief summary of your review.", "required": true}, "review": {"order": 2, "value-regex": "[\\S\\s]{1,200000}", "description": "Please provide an evaluation of the quality, clarity, originality and significance of this work, including a list of its pros and cons (max 200000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq . ***Please remember to file the Code-of-Ethics report. Once you submitted the review, a link to the report will be visible in the bottom right corner of your review.***", "required": true, "markdown": true}, "rating": {"order": 3, "value-dropdown": ["10: Top 5% of accepted papers, seminal paper", "9: Top 15% of accepted papers, strong accept", "8: Top 50% of accepted papers, clear accept", "7: Good paper, accept", "6: Marginally above acceptance threshold", "5: Marginally below acceptance threshold", "4: Ok but not good enough - rejection", "3: Clear rejection", "2: Strong rejection", "1: Trivial or wrong"], "required": true}, "confidence": {"order": 4, "value-radio": ["5: The reviewer is absolutely certain that the evaluation is correct and very familiar with the relevant literature", "4: The reviewer is confident but not absolutely certain that the evaluation is correct", "3: The reviewer is fairly confident that the evaluation is correct", "2: The reviewer is willing to defend the evaluation, but it is quite likely that the reviewer did not understand central parts of the paper", "1: The reviewer's evaluation is an educated guess"], "required": true}}, "forum": "zUMD--Fb9Bt", "replyto": "zUMD--Fb9Bt", "readers": {"description": "Select all user groups that should be able to read this comment.", "values": ["everyone"]}, "nonreaders": {"values": []}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"], "description": "How your identity will be displayed."}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+", "description": "How your identity will be displayed."}}, "expdate": 1607428800000, "duedate": 1606752000000, "multiReply": false, "readers": ["everyone"], "tcdate": 1602538127543, "tmdate": 1606915788056, "super": "ICLR.cc/2021/Conference/-/Official_Review", "signatures": ["OpenReview.net"], "writers": ["ICLR.cc/2021/Conference"], "invitees": ["ICLR.cc/2021/Conference/Paper1078/Reviewers", "OpenReview.net/Support"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Review"}}}, {"id": "Men_ZUaDys", "original": null, "number": 15, "cdate": 1606147026687, "ddate": null, "tcdate": 1606147026687, "tmdate": 1606147026687, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "-HQl7ebJiVV", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment", "content": {"title": "Further response to AnonReviewer1 ", "comment": "Thanks for the comments. We appreciate your feedback and we\u2019d like to take further discussions on the remaining concerns.\n\n##Non-linearity ##\n\nTo further address the concerns on the non-linearity issue, we update the paper with a newly added section (Sec. 4 in the latest version), which shows that under mild assumptions our main results are still applicable when non-linearity exists. Please refer to Sec.4 of the revised paper for detailed discussion.\n\n##ECC formulation ##\n\nWe update the formulation of ECC in the Appendix G. We find that categorizing ECC into the attention-based GCNs can lead to misunderstanding, Therefore, we remove the ECC from section 3.1.3 and only keep it in the Appendix B. Please let us know if you still have concerns.\n"}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "zUMD--Fb9Bt", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper1078/Authors|ICLR.cc/2021/Conference/Paper1078/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923863937, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment"}}}, {"id": "CN2C4trPnma", "original": null, "number": 14, "cdate": 1606146918692, "ddate": null, "tcdate": 1606146918692, "tmdate": 1606146918692, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "V_aMIeRjCg", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment", "content": {"title": "Update for non-linearity concerns", "comment": "To further address the concerns on the non-linearity issue, we update the paper with a newly added section (Sec. 4 in the latest version), which shows that under mild assumptions our main results are still applicable when non-linearity exists. Please refer to Sec.4 of the revised paper for detailed discussion."}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "zUMD--Fb9Bt", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper1078/Authors|ICLR.cc/2021/Conference/Paper1078/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923863937, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment"}}}, {"id": "vZb6um3VQrr", "original": null, "number": 13, "cdate": 1606146868101, "ddate": null, "tcdate": 1606146868101, "tmdate": 1606146868101, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "TI7mf0Uooc", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment", "content": {"title": "Update for non-linearity concerns", "comment": "To further address the concerns on the non-linearity issue, we update the paper with a newly added section (Sec. 4 in the latest version), which shows that under mild assumptions our main results are still applicable when non-linearity exists. Please refer to Sec.4 of the revised paper for detailed discussion."}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "zUMD--Fb9Bt", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper1078/Authors|ICLR.cc/2021/Conference/Paper1078/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923863937, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment"}}}, {"id": "-HQl7ebJiVV", "original": null, "number": 12, "cdate": 1606050409701, "ddate": null, "tcdate": 1606050409701, "tmdate": 1606050637066, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "Lu1Ayx-zhFT", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment", "content": {"title": "Response to the authors", "comment": "I would like to thank the authors for their rebuttal.\n\nI'm still of the opinion that this work is interesting and that it provides a good theoretical foundation for understanding GNNs by interpreting their various convolution filters as additional regularizers in the graph Fourier domain (while this might not be novel for vanilla-GCN, I am not aware of any work that extends these insights to other popular GNN variants):\n\n## Pros:\n\n* Theoretical foundations to unify GCN-based models\n* Proposal of a new regularization technique inspired by the introduced framework which seems to perform well in practice\n* My concerns regarding the experimental evaluation have been addressed (Table 2 and Table 3) and look convincing to me (although the training split seems to be different from the experiments in Table 1).\n\n## Cons:\n\n* As other reviewers reported, non-linearities are not considered which limits the impact of this work. As the authors state, this leads to substantial difficulty in theoretical analysis, but would strengthen the papers contribution and impact by a wide margin. In particular, since the importance of non-linearity in GCNs is still not well-understood as recent work indicates (e.g., SGC and APPNP).\n\n* Recent works on GNNs apply non-linear filters (e.g., ECC) or non-linear transformations (e.g., GIN). However, this work considers only linear operations or drops the non-linear transformation parts completely. While the proposed framework has the potential to unify linear filters, it does not look like it can do this for *any* graph-based convolutional filter (as the title claims).\n\n* I still don't see how ECC is compatible with the proposed framework (Eq. (18)), in particular because $\\bar{x}(i)$ and $\\bar{x}(j)$ should be transformed differently via $\\Theta_{j,i}$ (see Eq. (1) in the ECC paper)."}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/AnonReviewer1"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/AnonReviewer1"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "zUMD--Fb9Bt", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper1078/Authors|ICLR.cc/2021/Conference/Paper1078/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923863937, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment"}}}, {"id": "JZLs4NjS_h-", "original": null, "number": 6, "cdate": 1605973049934, "ddate": null, "tcdate": 1605973049934, "tmdate": 1605973323182, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "V_aMIeRjCg", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment", "content": {"title": "Response to AnonReviewer4", "comment": "We would first like to express our appreciation for your time and insightful comments. Please find our response to your concerns in the following:\n1.\t** Non-linear activations ** \n\nThanks for the valuable suggestion. Nonlinear activation is indeed important for deep neural networks. Unfortunately, nonlinearity also causes substantial difficulty for theoretical analysis. Many existing works on analyzing GCNs [1][2] only explore the properties of linear operations but still provide thoughtful insights. In our paper we follow these researches and start with linear operations to understand and relate different GCN models. \nDespite the lack of nonlinear activations, we believe that our framework is still valuable for the following reasons:\n\nFirst, the key ingredient that differentiates many popular graph neural networks (like GCN, PPNP, and GDC) is the way of designing linear filters, while their nonlinear activation layers are identical (e.g., relu). To analyze the relations and differences among these approaches, it might be sufficient to consider only the linear operations. By formulating various GCNs from the optimization perspective, insights towards understanding and comparing the key components of different GCNs can still be provided.\n\nSecond, recent work (e.g., SGC) has shown that even without nonlinear transformations, GCN can still yield competitive results.\n\n2.\t** Significance **\n\nAlthough we haven\u2019t incorporated non-linear activations in the unified framework, we consider our work still makes valuable contributions from two perspectives. First, as we have stated in the ** Non-linear activations ** part, our framework can provide new insights towards **understanding and comparing the key components of different GCNs**. Second, comparing with the classical approaches (by Mikhail Belkin and Xiaojin Zhu around 2004-06), despite that we both focus on the linear operation, we take a step forward from another direction, and try to understand and relate various **new GCN models** (e.g., attention-based, topology-based GCNs) in a unified framework. We provide new insights towards state-of-the-art GCN models and inspire to designing better models based on the framework.\n\n3.\t** Training time ** \n\nAs we have stated in section 4.1, we adopt an iterative algorithm to avoid the computation of Kronecker product and inverse operators. When combining with vanilla GCNs, the training time of our model is similar to GAT and AGNN and faster than APPNP. We have conducted experiments on the training time of baseline models and ours, and we update the results in the supplementary section (Appendix E).\n\nLastly, we are grateful for your time and we hope we have adequately addressed your concerns. We look forward to additional discussion.\n\n[1] Hoang, NT and T. Maehara. \u201cRevisiting Graph Neural Networks: All We Have is Low-Pass Filters.\u201d ArXiv abs/1905.09550 (2019): n. pag.\n[2] Loukas, Andreas. \u201cWhat graph neural networks cannot learn: depth vs width.\u201d ArXiv abs/1907.03199 (2020): n. pag.\n"}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "zUMD--Fb9Bt", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper1078/Authors|ICLR.cc/2021/Conference/Paper1078/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923863937, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment"}}}, {"id": "_PEBG1paYUI", "original": null, "number": 5, "cdate": 1605972934115, "ddate": null, "tcdate": 1605972934115, "tmdate": 1605972934115, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "l9TmkZxM89_", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment", "content": {"title": "Reponse to AnonReviewer3", "comment": "We would first like to express our appreciation for your time and insightful comments. Please find our response to your concerns in the following:\n1.\t**Novelty of the paper ** \n\nFirst, we consider the main contribution of our paper is formulating different GCNs in a unified framework. As far as we are concerned, this is the first work trying to **build connections among various GCN-based models**. Due to the success of GCN, numerous variants have been proposed from feature learning, architecture designing and many other directions. Several models are proposed from different angles while end up with similar formulations, e.g., GDC, APPNP and TAGCN. However, the similarities and differences are rarely investigated. Therefore, by establishing a unified framework, we show different modules with regularizers explicitly and relate GCN-based modules from a new perspective.\n\nThen, based on the unified framework, we additionally propose a novel regularizer to tackle oversmoothing. This approach no only achieves better performance, but also shows the feasibility of designing new regularizers based on the framework.\n\n2.\t**Detailed analysis on transforming the original graph ** \n\nWe have explored the equivalency of graph filters and transformations on the original graph before. However, the analysis is somewhat simple and straightforward, thus we didn\u2019t put it in our paper. For example, the attention-based filters can be interpreted as transferring the hard adjacency matrix to soft adjacency matrix with regard to the attention weights. The topology-based filters can be interpreted as transferring the adjacency matrix to a weighted sum of multiple orders of the original adjacency matrix. In this paper, we are more focused on the effect of various modules from the graph signal perspective, thus we omit the analysis towards the transformation over the graph. Thanks for the valuable suggestion, and we are happy to provide a detailed analysis in the supplementary section in case readers are interested.\n\n3.\t**Sensitive study on the additional hyper-parameter **\n\nWe appreciate your suggestions and we have conducted experiments. We update additional results in the supplementary section (Appendix F). \n\n4.\t**The minor comment ** \n\nThanks for pointing out and we are sorry for the confusion. By keeping the \\alpha_1, we want to keep the form of (21) the same as the unified framework defined in (18). \n\nLastly, we are grateful for your time and we hope we have adequately addressed your concerns. We look forward to additional discussion.\n"}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "zUMD--Fb9Bt", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper1078/Authors|ICLR.cc/2021/Conference/Paper1078/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923863937, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment"}}}, {"id": "_HW44yPA2vn", "original": null, "number": 4, "cdate": 1605972761834, "ddate": null, "tcdate": 1605972761834, "tmdate": 1605972761834, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "TI7mf0Uooc", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment", "content": {"title": "Response to AnonReviewer2: Part I", "comment": "We would first like to express our appreciation for your time and insightful comments. Please find our response to your concerns in the following:\n\n1.\t** Non-linear activations **\n\nThanks for the valuable suggestion. Nonlinear activation is indeed important for deep neural networks. Unfortunately, nonlinearity also causes substantial difficulty for theoretical analysis. Many existing works on analyzing GCNs [1][2] only explore the properties of linear operations but still provide thoughtful insights. In our paper, we follow these researches and start with linear operations to understand and relate different GCN models. \nDespite the lack of nonlinear activations, we believe that our framework is still valuable for the following reasons:\n\nFirst, the key ingredient that differentiates many popular graph neural networks (like GCN, PPNP, and GDC) is the way of designing linear filters, while their nonlinear activation layers are identical (e.g., relu). To analyze the relations and differences among these approaches, it might be sufficient to consider only the linear operations. By formulating various GCNs from the optimization perspective, insights towards understanding and comparing the key components of different GCNs can still be provided.\n\nSecond, recent work (e.g., SGC) has shown that even without nonlinear transformations, GCN can still yield competitive results.\n\n2.\t**Differences with regularization framework in vanilla-GCN **\n\nThe original GCN paper interprets the graph-based semi-supervised learning problem as adopting a graph Laplacian regularization term with supervised loss. Although the graph Laplacian regularization term is utilized in both frameworks, there still exist several differences:\n\nFirst, the framework formulated in GCN is a **learning-based** framework driven by supervised signals and back propagation. Therefore, interpretability of the model remains questionable and few insights are discussed in the GCN paper. By comparison, our proposed framework interprets graph filters as closed-form solutions (partly approximated) of **optimization problems**, and shows the property of the filters as various regularizers explicitly.\n\nSecond, our proposed framework has better **flexibility** and **potentiality**. Compared to GCN, our unified framework can formulate a variety of GCN-based models and build connections among GCN variants. Meanwhile, expert-designed modules can be implemented based on the unified framework and inspire new GCN models.\n"}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "zUMD--Fb9Bt", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper1078/Authors|ICLR.cc/2021/Conference/Paper1078/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923863937, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment"}}}, {"id": "qYadojTqAda", "original": null, "number": 3, "cdate": 1605972671820, "ddate": null, "tcdate": 1605972671820, "tmdate": 1605972671820, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "TI7mf0Uooc", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment", "content": {"title": "Response to AnonReviewer2: Part II", "comment": "3. **Differences with traditional label propagation framework **\n\nThe main differences between traditional label propagation framework and our work are two-fold. First, our paper proposes a more generalized framework and extends it to **formulating various new GCN models** (e.g., attention-based GCNs, topology-based GCNs). This provides a novel perspective to understand and relate different GCNs. Second, **novel regularizes** can be designed based on our framework and inspire new insights to designing better GCN models.\n\n4.\t**Connections between the proposed regularizer and PairNorm **\n\nThe original paper of PairNorm introduces two metrics, which are referred to as **node-wise** and **feature-wise** oversmoothing (eq (3) & (4) in their paper), respectively. However, the PairNorm algorithm fully relies on the first metric, while our regularizer is inspired by the second. As these two metrics are essentially different, our approach differs from PairNorm substantially.\n\nSpecifically, PairNorm is a **normalization technique** which designs a normalization layer to prevent unconnected **nodes** from getting closer. By comparison, ours is a **regularization technique** which introduces a regularizer to the objective function to maximize the distance between **features**. Moreover, PairNorm can be viewed as an individual layer, while our regularizer is incorporated in graph filters. Therefore, the two approaches tackle the oversmoothing problem from two different perspectives with different techniques, and can be viewed as complementary methods.\n\nIn addition, we find that feature-wise distance is an effective metric for quantifying oversmoothing. As we have stated in section 4.1, features tend to fall into the same subspace spanned by the dominated eigenvectors of the normalized adjacency matrix. Similar observations are also found in [3][4], showing that the distance between features (rather than nodes) shrink to 0 with sufficient number of layers, which is the leading cause of oversmoothing. \n\nEmpirically, PairNorm is more suitable when features are missing in the graph, where feature-wise oversmoothing is naturally alleviated. In comparison, our approach achieves consistent improvements in general settings when implemented on several SOTA GCNs.\n\nLastly, we are grateful for your time and we hope we have adequately addressed your concerns. We look forward to additional discussion.\n\n[1] Hoang, NT and T. Maehara. \u201cRevisiting Graph Neural Networks: All We Have is Low-Pass Filters.\u201d ArXiv abs/1905.09550 (2019): n. pag.\n\n[2] Loukas, Andreas. \u201cWhat graph neural networks cannot learn: depth vs width.\u201d ArXiv abs/1907.03199 (2020): n. pag.\n\n[3] Klicpera, Johannes et al. \u201cPredict then Propagate: Graph Neural Networks meet Personalized PageRank.\u201d ICLR (2019).\n\n[4] Li, Qimai et al. \u201cDeeper Insights into Graph Convolutional Networks for Semi-Supervised Learning.\u201d ArXiv abs/1801.07606 (2018): n. pag."}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "zUMD--Fb9Bt", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper1078/Authors|ICLR.cc/2021/Conference/Paper1078/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923863937, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment"}}}, {"id": "Lu1Ayx-zhFT", "original": null, "number": 2, "cdate": 1605971845084, "ddate": null, "tcdate": 1605971845084, "tmdate": 1605971845084, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "_oBYcrE87EB", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment", "content": {"title": "Response to AnonReviewer1", "comment": "We would first like to express our appreciation for your time and insightful comments. Please find our response to your concerns in the following:\n\n1. **Connections between the proposed regularizer and PairNorm **\n\nThe original paper of PairNorm introduces two metrics, which are referred to as **node-wise** and **feature-wise** oversmoothing (eq (3) & (4) in their paper), respectively. However, the PairNorm algorithm fully relies on the first metric, while our regularizer is inspired by the second. As these two metrics are essentially different, our approach differs from PairNorm substantially.\n\nSpecifically, PairNorm is a **normalization technique** which designs a normalization layer to prevent unconnected **nodes** from getting closer. By comparison, ours is a **regularization technique** which introduces a regularizer to the objective function to maximize the distance between **features**. Moreover, PairNorm can be viewed as an individual layer, while our regularizer is incorporated in graph filters. Therefore, the two approaches tackle the oversmoothing problem from two different perspectives with different techniques, and can be viewed as complementary methods.\n\nIn addition, we find that feature-wise distance is an effective metric for quantifying oversmoothing. As we have stated in section 4.1, features tend to fall into the same subspace spanned by the dominated eigenvectors of the normalized adjacency matrix. Similar observations are also found in [1][2], showing that the distance between features (rather than nodes) shrink to 0 with sufficient number of layers, which is the leading cause of oversmoothing. \n\nEmpirically, PairNorm is more suitable when features are missing in the graph, where feature-wise oversmoothing is naturally alleviated. In comparison, our approach achieves consistent improvements in general settings when implemented on several SOTA GCNs.\n\t\n2.\t**Experiment section ** \n\nWe appreciate your suggestions and we have conducted experiments on comparisons with other related approaches. We update the additional results and Performance of GCN on PPI in the experiment (Section 4.3). We would also like to point out that our main contribution is the unified framework, and the proposed algorithm is for showing the feasibility of designing new regularizers based on the framework.\n\n3.\t** ECC formulation **\n\nTruly ECC is different from other attention-based approaches as the weight normalization is not employed. To address the unrestricted weight for each node, we can add a mapping matrix \\Theta for signals in the attention regularizer as we have adopted in the concatenation formulation. (which turns the second form into \\sum_{p_{ij}||x(i)\\Theta-x(j)\\Theta||^2}) With this adaptation, we can formulate unweighted attention matrices, e.g., ECC. We are sorry for the confusion and we add the reformulation in the Appendix B.\n\nLastly, we are grateful for your time and we hope we have adequately addressed your concerns. We look forward to additional discussions.\n\n[1] Klicpera, Johannes et al. \u201cPredict then Propagate: Graph Neural Networks meet Personalized PageRank.\u201d ICLR (2019).\n\n[2] Li, Qimai et al. \u201cDeeper Insights into Graph Convolutional Networks for Semi-Supervised Learning.\u201d ArXiv abs/1801.07606 (2018): n. pag.\n"}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/Authors"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Authors"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. The effectiveness of the newly designed model is validated empirically.", "one-sentence_summary": "We propose a unified framework for convolution-based graph neural networks and provide a general methodology for evaluating and relating different graph learning modules.", "pdf": "/pdf/ccb08271660a1cade01473774368d671f3fb1c9e.pdf", "supplementary_material": "/attachment/c5ea4961ff3b9bbd90b8d22383a7dae25a651f25.zip", "code_of_ethics": "I acknowledge that I and all co-authors of this work have read and commit to adhering to the ICLR Code of Ethics", "paperhash": "pan|a_unified_framework_for_convolutionbased_graph_neural_networks", "reviewed_version_(pdf)": "https://openreview.net/references/pdf?id=aDO3iLeZne", "_bibtex": "@misc{\npan2021a,\ntitle={A Unified Framework for Convolution-based Graph Neural Networks},\nauthor={Xuran Pan and Shiji Song and Gao Huang},\nyear={2021},\nurl={https://openreview.net/forum?id=zUMD--Fb9Bt}\n}"}, "tags": [], "invitation": {"reply": {"content": {"title": {"order": 0, "value-regex": ".{1,500}", "description": "Brief summary of your comment.", "required": true}, "comment": {"order": 1, "value-regex": "[\\S\\s]{1,5000}", "description": "Your comment or reply (max 5000 characters). Add formatting using Markdown and formulas using LaTeX. For more information see https://openreview.net/faq", "required": true, "markdown": true}}, "forum": "zUMD--Fb9Bt", "readers": {"description": "Who your comment will be visible to. If replying to a specific person make sure to add the group they are a member of so that they are able to see your response", "values-dropdown": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"], "default": ["ICLR.cc/2021/Conference/Program_Chairs", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs"]}, "writers": {"values-copied": ["ICLR.cc/2021/Conference", "{signatures}"]}, "signatures": {"values-regex": "ICLR.cc/2021/Conference/Paper1078/AnonReviewer[0-9]+|ICLR.cc/2021/Conference/Paper1078/Authors|ICLR.cc/2021/Conference/Paper1078/Area_Chair[0-9]+|ICLR.cc/2021/Conference/Program_Chairs", "description": "How your identity will be displayed."}}, "expdate": 1610649480000, "final": [], "readers": ["everyone"], "nonreaders": [], "invitees": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/Area_Chairs", "ICLR.cc/2021/Conference/Program_Chairs", "OpenReview.net/Support"], "noninvitees": [], "tcdate": 1601923863937, "tmdate": 1610649509835, "super": "ICLR.cc/2021/Conference/-/Comment", "signatures": ["ICLR.cc/2021/Conference"], "writers": ["ICLR.cc/2021/Conference"], "id": "ICLR.cc/2021/Conference/Paper1078/-/Official_Comment"}}}, {"id": "V_aMIeRjCg", "original": null, "number": 2, "cdate": 1603795640339, "ddate": null, "tcdate": 1603795640339, "tmdate": 1605024536201, "tddate": null, "forum": "zUMD--Fb9Bt", "replyto": "zUMD--Fb9Bt", "invitation": "ICLR.cc/2021/Conference/Paper1078/-/Official_Review", "content": {"title": "GNN unified using old ideas of regularisation, but non-linearity not accounted", "review": "Summary: The paper shows that several graph networks (GCN, attention GCN, PPNP, residual) can be unified under a common framework of Laplacian-regularised optimisation. Subsequently, different types of regularisation are combined to propose a new method for graph transduction, which is then empirically evaluated.\n\nSignificance: Laplacian regularisation is a classical approach for formulating/justifying graph transduction algorithms (multiple papers by Mikhail Belkin and Xiaojin Zhu around 2004-06). It is interesting to see that so many graph networks can also be unified in the same framework. A unified framework does aid in both theoretical analysis and implementation of GCNs.\nHowever, the claims and derivation do not seem to account for the non-linear activation in the networks, and hence, significance of the work seems limited.\n\nQuality: As noted above, non-linearity is not considered which makes the derivation significantly simpler. Moreover, the first-order approximation is quite misleading since even the proof do not seem to consider non-linear activation. \nSince the proposed method combines multiple types of regularisation, it is expected to perform better than other networks. However, it is not clear if the training time increases due to the complex regularisation.\n\nClarity and orginality: The paper is otherwise well written / organised, and the theoretical contributions (although technically straightforward) seem original and somewhat interesting.\n\n\n", "rating": "5: Marginally below acceptance threshold", "confidence": "3: The reviewer is fairly confident that the evaluation is correct"}, "signatures": ["ICLR.cc/2021/Conference/Paper1078/AnonReviewer4"], "readers": ["everyone"], "nonreaders": [], "writers": ["ICLR.cc/2021/Conference", "ICLR.cc/2021/Conference/Paper1078/AnonReviewer4"], "details": {"replyCount": 0, "writable": false, "overwriting": [], "revisions": false, "forumContent": {"title": "A Unified Framework for Convolution-based Graph Neural Networks", "authorids": ["~Xuran_Pan1", "~Shiji_Song1", "~Gao_Huang1"], "authors": ["Xuran Pan", "Shiji Song", "Gao Huang"], "keywords": ["Graph Representation Learning", "Graph Convolution", "Graph Signal Processing", "Oversmoothing"], "abstract": "Graph Convolutional Networks (GCNs) have attracted a lot of research interest in the machine learning community in recent years. Although many variants have been proposed, we still lack a systematic view of different GCN models and deep understanding of the relations among them. In this paper, we take a step forward to establish a unified framework for convolution-based graph neural networks, by formulating the basic graph convolution operation as an optimization problem in the graph Fourier space. Under this framework, a variety of popular GCN models, including the vanilla-GCNs, attention-based GCNs and topology-based GCNs, can be interpreted as a same optimization problem but with different carefully designed regularizers. This novel perspective enables a better understanding of the similarities and differences among many widely used GCNs, and may inspire new approaches for designing better models. As a showcase, we also present a novel regularization technique under the proposed framework to tackle the oversmoothing problem in graph convolution. 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The authors also propose a novel regularization technique to approach the oversmoothing problem in graph convolution. Experiments on the standard settings of node classification on Citeseer, Cora, and Pubmed prove the effectiveness of the proposed regularization techniques. \n\nOverall, this is a very interesting paper, proposing a unified framework for different variants of convolution-based graph neural networks. However, I also have a few concerns:\n\n(1) The proposed framework is mainly designed for GNNs without considering the nonlinear transformation matrix. What if we have to consider the nonlinear transformation? Is the whole framework able to unify different GNNs?\n\n(2) In the case of linear GNNs (without nonlinear transformation matrix), it is actually not surprising formulating GNNs as a regularized optimization problem. 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{"poster":"Lukkran","date":"2016-05-21T07:25:54.130+0000","title":"perchè?","subforum":"Aiuto e supporto","up_votes":3,"down_votes":3,"body":"RIOT GAMES, vorrei sapere perchè una volta che accedo al gioco mi dice si è verificato un errore sconosciuto e non mi fa accedere alla chat PVP.Net ? vorrei sapere anche perchè mi da fastidio non comunicare con gli altri (anche se a volte ti risparmi gli insulti) ma il silenzio e il giocare da solo è brutto, volevo un' pò di PI bonus ma non posso nè invitare amici nella mia partita nè fare niente, se volessi giocare a urf e mi devo bannare io non so chi vogliono che banni. per favore risolvete\n\nP.S: mi scuso per eventuali errori grammaticali ma sono le nove e mezza del mattino e la mattina sono così più o meno {{sticker:zombie-nunu-bummed}}","replies":[{"poster":"sxrrxwland","date":"2016-05-21T07:31:15.309+0000","up_votes":2,"down_votes":0,"body":"Se vedi il bottoncino giallo in alto è un problema di tutti... La cosa che mi dà enormemente fastidio è che tutto ciò avvenga nel fine settimana con ip bonus, l'ultimo party ip weekend l'abbiamo avuto mesi fa e ora che arriva di nuovo per tutti, non possiamo invitare amici e quindi ottenere ip bonus... Best Trollata Ever {{champion:48}}","replies":[{"poster":"Yazurin","date":"2016-05-21T08:06:03.356+0000","up_votes":1,"down_votes":0,"body":"Metti in conto che c'è anche la URF e la gente vuole giocare con gli amici divertendosi e prendendo IP bonus.","replies":[]},{"poster":"Lukkran","date":"2016-05-21T07:35:47.898+0000","up_votes":1,"down_votes":0,"body":"ah grazie l'avevo visto un minuto fa e mi sono sentito un coglione grazie del commento e si, hai ragione, la più grande trollata dopo quella di paolocannone {{champion:48}}","replies":[]}]}]} |
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{"poster":"Batrix2","date":"2015-07-28T21:40:18.816+0000","title":"Suchen Mid/Jungler für Oepfelküechli","subforum":"Clans & Teams","up_votes":1,"down_votes":1,"body":"suchen noch einen Mid/Jungler für Teamranked","replies":[{"poster":"DerVollidiot","date":"2015-07-28T22:16:48.749+0000","up_votes":1,"down_votes":0,"body":"Ich würde ein Jungler sein, welche Division denn? bin Gold V","replies":[]},{"poster":"SPIN ElderSafe","date":"2015-07-28T22:08:41.106+0000","up_votes":1,"down_votes":0,"body":"ich würde ein midlaner sein^^","replies":[]}]} |
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{"poster":"Excorpion","date":"2018-04-29T16:10:53.983+0000","title":"No me quiero ir señor jg :C","subforum":"Memes & juegos","up_votes":46,"down_votes":5,"body":"https://i.gyazo.com/d2f224d183d0c801a88d898cb4c3043f.png","replies":[{"poster":"MagmaStriker","date":"2018-04-29T16:12:19.743+0000","up_votes":10,"down_votes":1,"body":"Borralo porfa es muy sad {{sticker:zombie-nunu-tears}}","replies":[{"poster":"prismleo","date":"2018-04-30T14:17:23.730+0000","up_votes":1,"down_votes":0,"body":"Disculpa Mi ignorancia pero recién estoy comenzando en el foro y no se como poner por decir eso “Gestos” Me podrias decir como se ponen pls?","replies":[{"poster":"theforumwillburn","date":"2018-04-30T20:40:16.742+0000","up_votes":1,"down_votes":0,"body":"Cuando vas a responder, un poco hacia la izquierda del botón de \"Publicar\" haces click en el gesto de Jinx y te abre la opción para elegir los demás gestos, más a la izquierda tenes ítems, hechizos, campeones y otras cosas para cambiar la fuente y escritura.","replies":[{"poster":"Excorpion","date":"2018-04-30T21:21:52.380+0000","up_votes":1,"down_votes":0,"body":"Solo en pc ***","replies":[]}]}]},{"poster":"Nuke","date":"2018-04-30T15:21:11.105+0000","up_votes":1,"down_votes":0,"body":"https://www.youtube.com/watch?v=N7BnzAsCOz8","replies":[]}]},{"poster":"Yitán","date":"2018-04-30T00:16:48.101+0000","up_votes":5,"down_votes":0,"body":"hay spoilers hasta en foros del lol, lpm","replies":[{"poster":"Hnk Kenshiro","date":"2018-04-30T11:46:37.016+0000","up_votes":1,"down_votes":1,"body":"¿Spoiler de?","replies":[{"poster":"nazareno 567","date":"2018-05-01T06:13:12.244+0000","up_votes":1,"down_votes":0,"body":"> [{quoted}](name=Hnk Kenshiro,realm=LAS,application-id=E47gYOsn,discussion-id=u3pEnusd,comment-id=00080001,timestamp=2018-04-30T11:46:37.016+0000)\n>\n> ¿Spoiler de?\n\nAvengers: Infinity War","replies":[]},{"poster":"Revòlver Ocelot","date":"2018-04-30T15:44:23.104+0000","up_votes":1,"down_votes":0,"body":"El manga del devorador, esa pic es del ultimo tomo que sacaron y alguno todavía no lo vimos. ~~Kappa~~","replies":[]}]},{"poster":"THK Spike","date":"2018-04-30T05:11:36.938+0000","up_votes":1,"down_votes":0,"body":"JAJAJA","replies":[]}]},{"poster":"Rohaerlyn","date":"2018-04-29T22:32:12.746+0000","up_votes":2,"down_votes":0,"body":"{{champion:238}} Te dije que te iba a matar \n{{champion:30}} Debiste comprar GA\nPENTAKILL \n{{sticker:garen-swing}}","replies":[]},{"poster":"Este No Es Zelos","date":"2018-04-29T16:15:54.112+0000","up_votes":3,"down_votes":1,"body":"Lo mismo dijeron los minigolems y varios items de jg.","replies":[]},{"poster":"Jigøku","date":"2018-04-30T00:02:42.928+0000","up_votes":1,"down_votes":2,"body":":o pero que es ese bicho :v","replies":[{"poster":"nazareno 567","date":"2018-05-01T06:16:14.467+0000","up_votes":3,"down_votes":1,"body":"https://imgur.com/a/4icdVID","replies":[{"poster":"Jigøku","date":"2018-05-01T12:38:05.963+0000","up_votes":1,"down_votes":0,"body":"Pero dime xD así entiendo","replies":[{"poster":"nazareno 567","date":"2018-05-01T22:22:31.167+0000","up_votes":1,"down_votes":0,"body":"Ese lobo te acompañaba cuando comprabas el item de jg \"devorador\", si mal no recuerdo tenías que matar a 20 monstruos de la jg para que el devorador evolucione y te dé lo que ahora sería la pasiva del {{item:3124}} \n\nPero fue eliminado en 2016 :c","replies":[]}]}]}]},{"poster":"LACTE4","date":"2018-12-12T20:08:38.867+0000","up_votes":1,"down_votes":0,"body":"Que lindo cuando despues de un milenio lo completabas y eras dios :'C","replies":[]},{"poster":"Rockett6","date":"2018-04-30T16:40:26.269+0000","up_votes":1,"down_votes":0,"body":"¿ Que es esa cosa?","replies":[{"poster":"Rockett6","date":"2018-04-30T16:41:06.866+0000","up_votes":1,"down_votes":0,"body":"Ya entendi, Marvel alert","replies":[]}]},{"poster":"MrAres","date":"2018-04-30T00:40:43.023+0000","up_votes":1,"down_votes":0,"body":"Nunca te olvidaremos viejo amigo :,c","replies":[]},{"poster":"Miroh","date":"2018-04-29T19:39:49.472+0000","up_votes":1,"down_votes":0,"body":"me encontraron :')","replies":[]},{"poster":"Agent Edgar Ross","date":"2018-04-29T19:11:55.956+0000","up_votes":1,"down_votes":0,"body":"{{sticker:cass-cry}} Borra eso por favor","replies":[]},{"poster":"Khada J","date":"2018-04-29T17:13:48.577+0000","up_votes":1,"down_votes":0,"body":"NOOOOOOOOOOOOOOO :´(","replies":[]},{"poster":"PajaCZ999","date":"2018-04-29T16:36:59.438+0000","up_votes":1,"down_votes":0,"body":"{{sticker:sg-soraka}}","replies":[]}]} |
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{"poster":"Evoz Psycho","date":"2016-12-18T14:18:01.560+0000","title":"Your own Build","subforum":"Champions & Gameplay","up_votes":1,"down_votes":3,"body":"So in the old Client you were able to make your own Build wich will be displayed instead of Recomended. Is this still possible with the new Client and if yes how?","replies":[{"poster":"OrangeBubble","date":"2016-12-18T15:56:50.777+0000","up_votes":1,"down_votes":0,"body":"No, not possible.","replies":[]},{"poster":"Good Guy Putin","date":"2016-12-18T15:00:42.357+0000","up_votes":1,"down_votes":0,"body":"Im Moment gibt es diese Funktioon nicht im neuen Client.","replies":[]},{"poster":"Alekra","date":"2016-12-18T14:54:09.699+0000","up_votes":1,"down_votes":0,"body":"Warum Englisch? Das ist das deutsche Forum\n\nEDIT: Zur Erklärung: Er hat schon in anderen Diskussionen deutsch geschrieben.","replies":[]}]} |
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[
"さといも牧場設置しゅーりょー*\\(^o^)/*東Ｍ-32a さといも牧場さんにて電ちゃんと時雨ちゃんです＼(^o^)／お待ちしてまーす！\n#C92 #c92 #艦これ #夏コミ #さといも牧場 https://t.co/wM2TdpptFB"
] |
{"poster":"MasterArcanist","date":"2016-03-25T22:48:58.115+0000","title":"[GAMEPLAY] Jhin - Bouncing Grenade Cancellation","subforum":"Report a Bug","up_votes":1,"down_votes":0,"body":"On Jhin, firing your Bouncing Grenade (Q) and autoattacking a target (it happens more frequently with the 4th shot) will cancel the bouncing grenade bounce completely. The shot should be fired while the grenade is still mid bounce. I would say it occurs about 10 to 20% of the time.","replies":[{"poster":"moonstones","date":"2016-03-28T18:10:31.590+0000","up_votes":2,"down_votes":0,"body":"Hey MasterArcanist! \n\nThanks for the report! We're looking to get a fix in for this ASAP.","replies":[]},{"poster":"LostFr0st","date":"2016-03-27T14:04:42.291+0000","up_votes":1,"down_votes":0,"body":"Riot is aware of the bug and working on it~\nhttp://boards.na.leagueoflegends.com/en/c/bug-report/jQYaup3c-gameplay-hn-jhin-q-bounce-only-twice?comment=0001","replies":[]}]} |
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