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paper_id stringlengths 19 21	paper_title stringlengths 8 170	paper_abstract stringlengths 8 5.01k	paper_acceptance stringclasses 18 values	meta_review stringlengths 29 10k	label stringclasses 3 values	review_ids list	review_writers list	review_contents list	review_ratings list	review_confidences list	review_reply_tos list
nips_2022_NI7moUOKtc	Debiased Self-Training for Semi-Supervised Learning	Deep neural networks achieve remarkable performances on a wide range of tasks with the aid of large-scale labeled datasets. Yet these datasets are time-consuming and labor-exhaustive to obtain on realistic tasks. To mitigate the requirement for labeled data, self-training is widely used in semi-supervised learning by i...	Accept	This paper proposed a novel Debiased self-training (DST) approach to reduce both data bias and self-training bias during SSL. The proposed method is simple and empirically seems quite effective. Reviewers are generally positive about the novelty of the method and significance of the results. While authors have tried to...	train	[ "MNldj4rUHSB", "h-glLyeY432", "hlP_XBCxNEU", "UL4gThotfQd", "p4II0lBrVaI", "XR0Lw7dYrRk", "YYLORyS8Jl0", "kf6TYThrO3P", "o7HgBwCoOL", "MJYPOh5P-7_", "jKq7_yJC5ov", "IV_xf4jVPC", "BnMIK-Elbt8" ]	[ "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We'd like to thank Reviewer G3sn again for providing an impressively insightful pre-rebuttal review, which has enabled us to make an effective response. We'd also thank you for carefully judging our feedback and acknowledging our work in the final review.", " Thanks for the enthusiastic reply from the authors. ...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 4 ]	[ "h-glLyeY432", "BnMIK-Elbt8", "UL4gThotfQd", "p4II0lBrVaI", "BnMIK-Elbt8", "YYLORyS8Jl0", "IV_xf4jVPC", "o7HgBwCoOL", "jKq7_yJC5ov", "nips_2022_NI7moUOKtc", "nips_2022_NI7moUOKtc", "nips_2022_NI7moUOKtc", "nips_2022_NI7moUOKtc" ]
nips_2022_pd6ipu3jDw	Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing	Learning in real-world multiagent tasks is challenging due to the usual partial observability of each agent. Previous efforts alleviate the partial observability by historical hidden states with Recurrent Neural Networks, however, they do not consider the multiagent characters that either the multiagent observation con...	Accept	All reviewers agree that this paper makes a good contribution in developing a novel transformer-based memory structure for MARL. The developed approach is evaluated through comprehensive and solid experiments. The authors have also clearly addressed the questions/concerns raised by the reviewers.	train	[ "glyeHm1r0uL", "p6a5mNg6q6t", "YKbITWdaknG", "gnsWFiQzFyF", "TnxWaDvOZhD", "d5qIbUcfnsQ", "GvfBGPSd7C", "oo_rfeSHwXP", "pTm1O8s_k4h", "P4Tr0D--pFK", "pi8bo1VM453" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for the response. I have no remaining concerns and still suggest to accept the paper.", " Hi authors,\n\nthank you for trying to cover my questions.\n\n[wall-clock time] yes, the comparison in wall-clock time is dependent on which hardware is used, but as you mentioned, if same hardware was used, then...	[ -1, -1, -1, -1, -1, -1, -1, -1, 6, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 3 ]	[ "oo_rfeSHwXP", "gnsWFiQzFyF", "GvfBGPSd7C", "TnxWaDvOZhD", "d5qIbUcfnsQ", "pi8bo1VM453", "P4Tr0D--pFK", "pTm1O8s_k4h", "nips_2022_pd6ipu3jDw", "nips_2022_pd6ipu3jDw", "nips_2022_pd6ipu3jDw" ]
nips_2022_kyY4w4IgtM8	Sharing Knowledge for Meta-learning with Feature Descriptions	Language is an important tool for humans to share knowledge. We propose a meta-learning method that shares knowledge across supervised learning tasks using feature descriptions written in natural language, which have not been used in the existing meta-learning methods. The proposed method improves the predictive perfor...	Accept	This paper presents a novel meta-learning approach based on learning a sentence encoder which maps feature descriptions to embeddings. The sentence encoder is shown to generalize to new tasks during the test phase, hence allowing few-shot learning. The main concern raised by the reviewers was about the use of only two ...	train	[ "jSdJE1-nBa1", "zwe2qC4O-Qi", "Z2iNMkdAXuD", "mh7ojlizpSk", "NHc9-6Ss-zW", "nraSoK-9UW", "xxFXC9XmR5B", "LXGKjsbz1xV" ]	[ "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for your constructive comments.\n\n> It looks like the only difference between the proposed method and a baseline (MDK + B) is the usage of the feature encoder (Fig 1), which is a 3 layer neural network. It looks like the authors agree with that as well (line 220). So the technical novelty (although gui...	[ -1, -1, -1, -1, 5, 6, 4, 7 ]	[ -1, -1, -1, -1, 3, 3, 4, 3 ]	[ "LXGKjsbz1xV", "xxFXC9XmR5B", "nraSoK-9UW", "NHc9-6Ss-zW", "nips_2022_kyY4w4IgtM8", "nips_2022_kyY4w4IgtM8", "nips_2022_kyY4w4IgtM8", "nips_2022_kyY4w4IgtM8" ]
nips_2022_YxUdazpgweG	MultiScan: Scalable RGBD scanning for 3D environments with articulated objects	We introduce MultiScan, a scalable RGBD dataset construction pipeline leveraging commodity mobile devices to scan indoor scenes with articulated objects and web-based semantic annotation interfaces to efficiently annotate object and part semantics and part mobility parameters. We use this pipeline to collect 230 scans ...	Accept	The reviewers tend to agree on the value of this 3D dataset, but point to some questions about labelling and accuracy. The rebuttal very convincingly addresses these points, clarifying the novelty and value of this new dataset. I agree with the authors that datasets are clearly in scope for the main NeurIPS program a...	test	[ "SnjXEVQ8Vm2", "hGjTYegkgu", "fS8cfhPUsxO", "g9U8dcH7hP", "W0JTrPUrMO8x", "mLzE2MzwYtc", "yLHZ0mfWAq", "K5ADA_8ixwL", "XKWPZvuyPI", "sG-YfIucLF", "VTSCtlgUGnr", "6E4lU7FKknX", "biZuN7V3kJj" ]	[ "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We thank the reviewer for their effort in reviewing our paper and recognize the reviewer's opinion. However, we would like to point out that the NeurIPS call for paper explicitly lists \"Infrastructure (e.g., datasets, competitions, implementations, libraries)\" as one of the paper topics sought by the main tra...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 3 ]	[ "hGjTYegkgu", "XKWPZvuyPI", "yLHZ0mfWAq", "K5ADA_8ixwL", "XKWPZvuyPI", "sG-YfIucLF", "biZuN7V3kJj", "6E4lU7FKknX", "VTSCtlgUGnr", "nips_2022_YxUdazpgweG", "nips_2022_YxUdazpgweG", "nips_2022_YxUdazpgweG", "nips_2022_YxUdazpgweG" ]
nips_2022_qq84D17BPu	Toward Equation of Motion for Deep Neural Networks: Continuous-time Gradient Descent and Discretization Error Analysis	We derive and solve an ``Equation of Motion'' (EoM) for deep neural networks (DNNs), a differential equation that precisely describes the discrete learning dynamics of DNNs. Differential equations are continuous but have played a prominent role even in the study of discrete optimization (gradient descent (GD) algorithm...	Accept	Reviewers were unanimous in recommending that the paper be accepted, and I accordingly recommend the same. I encourage the authors to take into account suggestions made by reviewers so as to further improve the text in the camera-ready version.	test	[ "AqAhq4j-fb", "KQgPqkd6lCc", "t0Cfu9_AZjx", "EXsuZlV5WIm", "OqeDadyeolJw", "tq2sm42Fpnm", "gZNtkH7td47i", "T6EyO-po4xw", "D20lsHVxobp", "y6_7_ZmMu3o", "wG_B2fsmud", "wXJelpaxe_-", "m2ublMtaNAc", "Iz50w-RRmB", "oy8p_VG_H5C", "w9yZ-gYqS5", "L-ZkcQZ90xd", "X_Fgcbk4OfT", "EJ1OTwhJ3xD...	[ "author", "official_reviewer", "author", "official_reviewer", "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_r...	[ " We really appreciate your suggestions!\nUsing a tiny synthetic dataset and an extremely small network would be a nice idea.\nWe will keep trying for possible future updates.\nWe agree it would make our paper much stronger.", " This reasoning is understandable and I accept it. Could it be possible on a network o...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 6, 7, 8 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 3, 3 ]	[ "KQgPqkd6lCc", "gZNtkH7td47i", "EXsuZlV5WIm", "y6_7_ZmMu3o", "tq2sm42Fpnm", "m2ublMtaNAc", "T6EyO-po4xw", "D20lsHVxobp", "MzXKD3ywbEb", "wG_B2fsmud", "EJ1OTwhJ3xD", "m2ublMtaNAc", "X_Fgcbk4OfT", "oy8p_VG_H5C", "L-ZkcQZ90xd", "nips_2022_qq84D17BPu", "nips_2022_qq84D17BPu", "nips_202...
nips_2022_QFQoxCFYEkA	DENSE: Data-Free One-Shot Federated Learning	One-shot Federated Learning (FL) has recently emerged as a promising approach, which allows the central server to learn a model in a single communication round. Despite the low communication cost, existing one-shot FL methods are mostly impractical or face inherent limitations, \eg a public dataset is required, clients...	Accept	This work proposes a new one-shot FL algorithm. It consists of two steps on the server: a data generation step that trains a GAN to synthesize data utilizing the local models and a distillation step that distills the ensembles local models using the generated data. The method has several advantages in comparison with o...	train	[ "Lg1fP8eq_zo", "GfW2Dp7GWK", "zQoMREJaEQJ1", "3kaITUVELstv", "-hRE4n1ihee", "qkRAm9yoCH9", "xUsK_edVQ_", "9-lTTxgIgfg", "uw3aVFOFvwD", "4I0WqBZPz6W", "CiwZuDY7r9O", "GQ27_-i_f5X", "2y71PkQ1vb4", "ChTm8qxpsaM", "PRrMzeha2kj", "FmHfLYha6an" ]	[ "official_reviewer", "official_reviewer", "author", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " i have updated my score, thanks.", " Hi\n\nThank you for your detailed response and I have improved your score. ", " Dear Reviewer fNZT,\n\nThank you again for your support of our work and valuable feedback! We tried our best to address all mentioned concerns/problems. Are there unclear explanations? We coul...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 8, 7, 8 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 5, 4, 4 ]	[ "xUsK_edVQ_", "zQoMREJaEQJ1", "PRrMzeha2kj", "2y71PkQ1vb4", "qkRAm9yoCH9", "9-lTTxgIgfg", "GQ27_-i_f5X", "PRrMzeha2kj", "PRrMzeha2kj", "FmHfLYha6an", "ChTm8qxpsaM", "2y71PkQ1vb4", "nips_2022_QFQoxCFYEkA", "nips_2022_QFQoxCFYEkA", "nips_2022_QFQoxCFYEkA", "nips_2022_QFQoxCFYEkA" ]
nips_2022_kImIIKGqDFA	Large-batch Optimization for Dense Visual Predictions	Training a large-scale deep neural network in a large-scale dataset is challenging and time-consuming. The recent breakthrough of large-batch optimization is a promising way to tackle this challenge. However, although the current advanced algorithms such as LARS and LAMB succeed in classification models, the complicate...	Accept	The authors describe a new method of large-batch optimisation for dense prediction computer vision tasks. The reviewers appreciate the simplicity of the method, convincing experiments and the potential practical importance. AC recommends acceptance.	train	[ "fuuyAj-Zwmx", "kyVABKuuTdV", "47H_oAl-m8P", "r7ga24fUZXZ", "6ZWFIaux64v", "M_4W8U5AYSM", "YmwI94VBbV6", "Q-sfGuAHgGT", "Si4jFbZ2JWj", "0TPnDMFk3wu", "11RhDmpM_Oa", "d2k7q0F7EVh", "T-RylbySvly", "ayqSR-1EV71", "VZeyRh3unE_", "vLePTGS36Gn", "WLLtGj3ZObn", "cUjnhTO9-fc", "vh9tDLrEx...	[ "author", "official_reviewer", "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Dear Reviewer KpQK,\n\nWe sincerely thank the reviewer for the constructive feedback and support!", " I would like to thank the authors for addressing my questions. Also, I appreciate my fellow reviewers' comments that lead to in-depth discussions with the authors.\n\nThe authors well addressed my concerns. Spe...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 6, 4, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 3, 3 ]	[ "kyVABKuuTdV", "cUjnhTO9-fc", "r7ga24fUZXZ", "ayqSR-1EV71", "M_4W8U5AYSM", "Q-sfGuAHgGT", "_cLFnqNu5vL", "vh9tDLrExpA", "nips_2022_kImIIKGqDFA", "11RhDmpM_Oa", "_cLFnqNu5vL", "T-RylbySvly", "cUjnhTO9-fc", "WLLtGj3ZObn", "vLePTGS36Gn", "vh9tDLrExpA", "nips_2022_kImIIKGqDFA", "nips_2...
nips_2022_35I4narr5A	Few-Shot Continual Active Learning by a Robot	In this paper, we consider a challenging but realistic continual learning problem, Few-Shot Continual Active Learning (FoCAL), where a CL agent is provided with unlabeled data for a new or a previously learned task in each increment and the agent only has limited labeling budget available. Towards this, we build on the...	Accept	All reviewers appreciated the importance of the problem being tackled, and the effectiveness of the proposed method. There were a number of concerns about ablations and use of pre-trained feature extractors, but these have been sufficiently addressed in the authors' rebuttal. I agree with the reviewers in recommending ...	train	[ "VnRpvUYZ2tI", "tzSh4pv1CMv", "gLiDdSXDWix", "SWqVULGF5U4", "OE-fiT_6A5m", "brcdAE7VBVd" ]	[ "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We thank you for your insightful comments and have used these comments to improve the paper.\n\nWeaknesses:\n\nMemory Usage: We have added a discussion about the memory usage of all the approaches in the paper (L 258-271). In particular, GBCL requires only 0.97 MB of space to store GMMs of the previous classes. I...	[ -1, -1, -1, 5, 5, 6 ]	[ -1, -1, -1, 3, 5, 3 ]	[ "brcdAE7VBVd", "OE-fiT_6A5m", "SWqVULGF5U4", "nips_2022_35I4narr5A", "nips_2022_35I4narr5A", "nips_2022_35I4narr5A" ]
nips_2022_s7SukMH7ie9	Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks	Adversarial training (AT) with imperfect supervision is significant but receives limited attention. To push AT towards more practical scenarios, we explore a brand new yet challenging setting, i.e., AT with complementary labels (CLs), which specify a class that a data sample does not belong to. However, the direct comb...	Accept	This paper focuses on a significant and challenging problem: adversarial training (AT) with complementary labels. A naive combination of AT with existing complementary learning techniques fails to achieve good performance. The authors conduct both theoretical and empirical analyses of this phenomenon and identified tw...	train	[ "tLaYQLJoIgX", "Yvkkotsj0dO", "91BuuBK9q_t", "BPTYboF200m", "-taFj7xoiKPp", "wIIszxf11eP", "T-K_K-JbzBZ", "rBUqOzjChV3", "vb5Bqa2ROSp", "MmF1rhW5Pl2", "9xvb8fTBBF6", "YiGAFtkXZz", "6e-wYzVGJsy", "GGVK5p28IC", "OOFm6Z2i248e", "IiWr7mal4jxs", "LTTDjAk26Zg", "SYs7QX0VnU-", "C8dUB90z...	[ "official_reviewer", "author", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_...	[ " Thanks the author for the through response and sorry for the late reply. The author has addressed most of my concerns, so I would raise my initial score and recommend this work.", " Dear Reviewer Jbnu,\n\nWould you mind acknowledging our rebuttal? As the discussion due is approaching, if you still have some que...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 8, 6, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 4, 4 ]	[ "q4E_h-xfUUc", "q4E_h-xfUUc", "q4E_h-xfUUc", "q4E_h-xfUUc", "OOFm6Z2i248e", "6e-wYzVGJsy", "nips_2022_s7SukMH7ie9", "C8dUB90z2or", "nips_2022_s7SukMH7ie9", "q4E_h-xfUUc", "q4E_h-xfUUc", "q4E_h-xfUUc", "D92bm06NeyQ", "C8dUB90z2or", "C8dUB90z2or", "SYs7QX0VnU-", "SYs7QX0VnU-", "nips_...
nips_2022_DGwX7wSoC-	Stationary Deep Reinforcement Learning with Quantum K-spin Hamiltonian Equation	A foundational issue in deep reinforcement learning (DRL) is that \textit{Bellman's optimality equation has multiple fixed points}---failing to return a consistent one. A direct evidence is the instability of existing DRL algorithms, namely, the high variance of cumulative rewards over multiple runs. As a fix of this p...	Reject	The paper proposes to add a regularisation term H to RL algorithms in order to work around issues caused by the multiple fixed points of the Bellman’s optimality equation. The added H term is inspired by quantum field theory, specifically the K-spin Ising model. All reviewers thought this was an interesting idea, but b...	train	[ "u0GE2bFfrf", "3nHlaClIgP9", "YlGgTa6ideC", "Ib90PbzwOEx", "3mtHRjay2s3", "Q2BP7OYq4l", "PeIbuVsHfS", "Dr_eklqeIRL", "_Y8eI4Qyivp", "2G3QBX5tBZ4", "Tf6OPfb20QI", "gEuv_7cukjg", "E48uwlhVFLb", "fXOT2Umw8mw", "zgiUUrgpkmS", "km2lSDnl8a3", "kUSX5cE6uoF", "rHkhf77PymIS", "ih8Veh64rSC...	[ "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer",...	[ " The authors sincerely thank all reviewers and area chair. The authors enjoy the discussions and are happy that some key points reached a consensus. \n\nTo recap, this work has made the following major contributions.\n1. Per Reviewer 65t2 and Reviewer Reviewer UzCH’s suggestion, the authors added Appx. E to includ...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 3, 5, 4 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 4, 3 ]	[ "nips_2022_DGwX7wSoC-", "3mtHRjay2s3", "Ib90PbzwOEx", "2G3QBX5tBZ4", "Q2BP7OYq4l", "PeIbuVsHfS", "_Y8eI4Qyivp", "Tf6OPfb20QI", "fXOT2Umw8mw", "rHkhf77PymIS", "gEuv_7cukjg", "E48uwlhVFLb", "ih8Veh64rSC", "zgiUUrgpkmS", "QMXeup90k36", "48QfxQ3EYmM", "rHkhf77PymIS", "df-3O7rWju", "B...
nips_2022_kHrE2vi5Rvs	Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization	Deep reinforcement learning (DRL)-based combinatorial optimization (CO) methods (i.e., DRL-NCO) have shown significant merit over the conventional CO solvers as DRL-NCO is capable of learning CO solvers less relying on problem-specific expert domain knowledge (heuristic method) and supervised labeled data (supervised l...	Accept	All reviewers agree that the paper presents interesting results, hence I recommend acceptance. On the other hand there are several issues which need to be addressed in the final version of the paper: 1. The authors should add the experimental results listed in the responses, as these demonstrate more convincingly the s...	train	[ "wlnh4kdd-Ak", "W_MdHXC4Gc", "FmCL282S6Rz", "gpTtFwt34sb", "-GkwaHQvMN9", "vIGGjgve-4b", "tjfPV_fIkw", "DMDTe586xNL", "CgQtXscPaM", "kwo2irW1MD", "zYmVM69pJ11", "19v1ZJ1bPA", "MOhzeoPFroy", "D9w-HR-JryC", "018NFbibjUx", "BbpQrVofgkA", "XyXLAD3rdq6", "rDXFlM_zbcQ", "TbhJz1v8V_M", ...	[ "official_reviewer", "author", "official_reviewer", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", ...	[ " Thank you for addressing my concerns regarding the claims on expressive power and hard vs. soft invariant learning.\n\nI find the updated Figure 1 and accompany text more convincing. I acknowledge that the previously made claims regarding the expressive power of ENNs and the required expressive power for combinat...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4 ]	[ "W_MdHXC4Gc", "FmCL282S6Rz", "gpTtFwt34sb", "tjfPV_fIkw", "czJ_Nqv19cM", "DMDTe586xNL", "j1rjzzhov7", "kwo2irW1MD", "018NFbibjUx", "zYmVM69pJ11", "19v1ZJ1bPA", "MOhzeoPFroy", "D9w-HR-JryC", "Xcz0e2MbDJT", "BbpQrVofgkA", "XyXLAD3rdq6", "rDXFlM_zbcQ", "j1rjzzhov7", "czJ_Nqv19cM", ...
nips_2022_PZtIiZ43E2R	List-Decodable Sparse Mean Estimation	Robust mean estimation is one of the most important problems in statistics: given a set of samples in $\mathbb{R}^d$ where an $\alpha$ fraction are drawn from some distribution $D$ and the rest are adversarially corrupted, we aim to estimate the mean of $D$. A surge of recent research interest has been focusing on the ...	Accept	This paper studies the problem of list-decodable mean estimation under the assumption that the true mean is sparse and the clean distribution is Gaussian with identity covariance. In this setting, we are given n data points and a parameter $0<\alpha \leq 1/2$ such that: (1) an unknown $\alpha$-fraction of the dataset...	train	[ "2U5M9o7uA3u", "nctcBLhkWwq", "kI-b7SFliXw", "2Sxc3h-pO1v", "K-8gCOWBdlFr", "bdY3wuzpdLg", "jhCHB0SX87", "3jydUowCshb", "fyw3cJQeIAh", "Djyzc4Bizay", "ftDFbFtKV19" ]	[ "official_reviewer", "author", "author", "author", "official_reviewer", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for the response. After reading the response and also other reviews, I would like to adjust my scores. However, I still have doubt on the technical novelty and the presentation for it in the manuscript, which in part also pointed out by Reviewer 7URr. Since I need to evaluate the paper as submitted, I t...	[ -1, -1, -1, -1, -1, -1, -1, -1, 5, 7, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 4 ]	[ "3jydUowCshb", "bdY3wuzpdLg", "fyw3cJQeIAh", "K-8gCOWBdlFr", "jhCHB0SX87", "ftDFbFtKV19", "Djyzc4Bizay", "fyw3cJQeIAh", "nips_2022_PZtIiZ43E2R", "nips_2022_PZtIiZ43E2R", "nips_2022_PZtIiZ43E2R" ]
nips_2022_vK53GLZJes8	The Pitfalls of Regularization in Off-Policy TD Learning	Temporal Difference (TD) learning is ubiquitous in reinforcement learning, where it is often combined with off-policy sampling and function approximation. Unfortunately learning with this combination (known as the deadly triad), exhibits instability and unbounded error. To account for this, modern Reinforcement Learn...	Accept	This paper presents a counterexample-driven analysis of regularization in TD learning with function approximation. Despite the paper's simplicity, the reviewers unanimously though there was a good contribution being made here, and I agree. Highlights include a clarity of presentation and new insights into what is know...	val	[ "FKKbT7FLuK0", "w-WAZ0KhMd", "8SA5Wlco-VD7", "KTA6iAqWO8d", "Y_6Pb03oYWx", "yhO1N-HI9p", "hY47VQ99s2j", "balME3sPHm", "5dhVt5HWfFj", "RtUBEJYenPf", "wPo-yeBbV89", "RwZjvughZMA" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for the response. I have edited my review/score upward after reading your clarifications. ", " Thank you for your answers! The authors have addressed my questions and I appreciate the additional experiments the authors provided.", " I thank the authors for their additional experiments and other upda...	[ -1, -1, -1, -1, -1, -1, -1, -1, 7, 7, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 3, 3 ]	[ "yhO1N-HI9p", "balME3sPHm", "Y_6Pb03oYWx", "hY47VQ99s2j", "RwZjvughZMA", "wPo-yeBbV89", "RtUBEJYenPf", "5dhVt5HWfFj", "nips_2022_vK53GLZJes8", "nips_2022_vK53GLZJes8", "nips_2022_vK53GLZJes8", "nips_2022_vK53GLZJes8" ]
nips_2022_mvbr8A_eY2n	Optimal Efficiency-Envy Trade-Off via Optimal Transport	We consider the problem of allocating a distribution of items to $n$ recipients where each recipient has to be allocated a fixed, pre-specified fraction of all items, while ensuring that each recipient does not experience too much envy. We show that this problem can be formulated as a variant of the semi-discrete opti...	Accept	Executive summary: The problem considered in this paper is as follows: There is a distribution over items X \subseteq [0,\bar{x}]^n where x_i denotes the value of the item to recipient i. There are also matching constraints {p_i}_{i \in N}, which require that each agent should be matched a p_i fraction pf the times. T...	train	[ "6e5ZbDh3kB", "D4sFqM63OCF", "DrqrED4_r6", "rUAZtQzAMS_", "FqokmmbpZfe", "DZ6ISIdBLFj", "Y8EC0xph9i7", "cOyDSjzknnw", "b3KCWxGn9Oc", "gjNubjL1wj4", "kC5nMJvTed2", "T4yQSXCVJ1F", "uqsFI5ejxS0", "1o13chfEk7X" ]	[ "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank the authors for the response. I will keep my score unchanged. I encourage authors to do a more extensive literature review and compare the results and methods in the future version.", " Thank the authors for the comments, which confirm my original thoughts about this paper. For this reason, I will stick t...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 7, 5, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 3, 3, 3 ]	[ "gjNubjL1wj4", "b3KCWxGn9Oc", "FqokmmbpZfe", "DZ6ISIdBLFj", "Y8EC0xph9i7", "cOyDSjzknnw", "1o13chfEk7X", "uqsFI5ejxS0", "T4yQSXCVJ1F", "kC5nMJvTed2", "nips_2022_mvbr8A_eY2n", "nips_2022_mvbr8A_eY2n", "nips_2022_mvbr8A_eY2n", "nips_2022_mvbr8A_eY2n" ]
nips_2022_NN_TpS5dpo5	Physically-Based Face Rendering for NIR-VIS Face Recognition	Near infrared (NIR) to Visible (VIS) face matching is challenging due to the significant domain gaps as well as a lack of sufficient data for cross-modality model training. To overcome this problem, we propose a novel method for paired NIR-VIS facial image generation. Specifically, we reconstruct 3D face shape and refl...	Accept	The paper received 3 positive reviews. The reviewers all lean towards acceptance after the rebuttal. Overall this work can be of large interest to the community working on NIR-VIS Recognition. But I hope the authors will present additional visualized results, as suggested by the reviewers.	train	[ "LAfiyyEDufW", "HtoeE3PK9-", "xxISs1sQozF0", "yvctP-Hs8gE", "rYvySiUn702", "Sj7wt6KCf94", "qQeilzKJpJm", "Pn6IESwYeA9" ]	[ "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for your answers. They addressed my concerns pre-rebuttal.\nI decide to keep my Accept score.", " We sincerely thank all reviewers for their valuable comments and insightful advice on our paper. We are pleased to see that all reviewers give highly positive ratings (one accept and two borderline accepts)....	[ -1, -1, -1, -1, -1, 7, 5, 5 ]	[ -1, -1, -1, -1, -1, 3, 5, 4 ]	[ "rYvySiUn702", "nips_2022_NN_TpS5dpo5", "Pn6IESwYeA9", "qQeilzKJpJm", "Sj7wt6KCf94", "nips_2022_NN_TpS5dpo5", "nips_2022_NN_TpS5dpo5", "nips_2022_NN_TpS5dpo5" ]
nips_2022_i7WqjtdD0u	Learning With an Evolving Class Ontology	Lifelong learners must recognize concept vocabularies that evolve over time. A common yet underexplored scenario is learning with class labels over time that refine/expand old classes. For example, humans learn to recognize ${\tt dog}$ before dog breeds. In practical settings, dataset $\textit{versioning}$ often introd...	Accept	The setting of evolving and refining classes over time is certainly a practical one in domains such as text classification. This paper offers some insights on questions like whether the entire data should be relabeled, or can one achieve near optimal performance by labeling only the new chunk. The paper concludes that ...	train	[ "RnK-1QjrKX", "xXkA6HloE7w", "3IiD-LeZ6lX", "UWp470cV8G7", "FhzJ-CsUDSD", "ipYiMikSC52", "0JLuh8-PMc", "GPVb_QHC_FY", "PBl3sqOd5M2", "h3ETQ0iGko", "E_uwV6_trR", "nSo92ZH_wMJ", "I0D9lbZHJbo", "VXQtlKLsLF2", "h96p-BtWSuC" ]	[ "author", "author", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you Reviewer YxYF for your interaction and upgraded rating!\n\nAgain, we appreciate your positive attitude with \"no reservation about the quality of the submission\" (e.g., clarity and well-organized paper structure, the sound experimental setup and proposed models, novel setting of LECO, novel approach...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 5, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 3 ]	[ "UWp470cV8G7", "3IiD-LeZ6lX", "E_uwV6_trR", "PBl3sqOd5M2", "ipYiMikSC52", "GPVb_QHC_FY", "GPVb_QHC_FY", "h96p-BtWSuC", "h3ETQ0iGko", "VXQtlKLsLF2", "nSo92ZH_wMJ", "I0D9lbZHJbo", "nips_2022_i7WqjtdD0u", "nips_2022_i7WqjtdD0u", "nips_2022_i7WqjtdD0u" ]
nips_2022_x2WTG5bV977	The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and their Empirical Equivalence	Recently, it has been observed that a transfer learning solution might be all we need to solve many few-shot learning benchmarks -- thus raising important questions about when and how meta-learning algorithms should be deployed. In this paper, we seek to clarify these questions by 1. proposing a novel metric -- the {...	Reject	The paper performs some empirical study between transfer learning and MAML (as a meta-learning method) through the lens of task diversity. When the task diversity is low, the authors claim that the performance of MAML and transfer learning methods are similar under a fair comparison (e.g. same architecture, optimizer e...	train	[ "ZW9MPODnxe", "W8i2v2Qt1Gh", "OiezYFIryg", "GX75BQ5JVfW", "6AafxDJfqiL", "KAfrK-mJAgp", "i6zPBBaOkKh", "HVpRm3lwQip", "4-O5PLN94Fb", "uhVB3MINJj", "W96vJbpx-Si", "jema0OvfYf" ]	[ "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you the authros for addressing my concerns raised in the initial review. However, I am not satisfied with the reply from the authors. Please see my comments below.\n\n> Providing different results using different probe networks is more superior than an emsemble approach\n\nThis is quite arguable and I will ...	[ -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 3 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 4, 4 ]	[ "KAfrK-mJAgp", "KAfrK-mJAgp", "jema0OvfYf", "KAfrK-mJAgp", "KAfrK-mJAgp", "W96vJbpx-Si", "uhVB3MINJj", "4-O5PLN94Fb", "nips_2022_x2WTG5bV977", "nips_2022_x2WTG5bV977", "nips_2022_x2WTG5bV977", "nips_2022_x2WTG5bV977" ]
nips_2022_BWEGx_GFCbL	Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks	While significant theoretical progress has been achieved, unveiling the generalization mystery of overparameterized neural networks still remains largely elusive. In this paper, we study the generalization behavior of shallow neural networks (SNNs) by leveraging the concept of algorithmic stability. We consider gradie...	Accept	The paper studies the generalization of a committee machine using algorithm stability. Compared to previous works, the authors obtain similar generalization error for smaller width for both GD and SGD. Reviewers had some conflicting opinions about this paper, with major concerns on the limited novelty compared to [46] ...	train	[ "9b6r2YXH-m", "p6O-DOk__zp", "tX9zIgPYAgA", "i8QMqeNKGzR", "YD4v72-bbLu", "fyo4MR6Xi6K", "dL2vXim_CVg", "bvwMr7tFc9", "09ff1HjLjC", "rqkQrjcnZiW", "pa2aTKfkNEJ", "nYV1gDB6ZRq", "8Zxp6IzO-T_", "PBxpm46PYkm" ]	[ "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the nice suggestion. We will follow your advice and will move the proof ideas of GD and SGD to the main text in the revised version.", " Thanks for the clarification of the role of Assumption 3 particularly in Theorem 6. The added sections in the appendix during the rebuttal on the proof ideas of GD ...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 7, 5, 6, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 2, 3, 2 ]	[ "p6O-DOk__zp", "dL2vXim_CVg", "fyo4MR6Xi6K", "nips_2022_BWEGx_GFCbL", "PBxpm46PYkm", "8Zxp6IzO-T_", "nYV1gDB6ZRq", "pa2aTKfkNEJ", "rqkQrjcnZiW", "nips_2022_BWEGx_GFCbL", "nips_2022_BWEGx_GFCbL", "nips_2022_BWEGx_GFCbL", "nips_2022_BWEGx_GFCbL", "nips_2022_BWEGx_GFCbL" ]
nips_2022_V88BafmH9Pj	A Contrastive Framework for Neural Text Generation	Text generation is of great importance to many natural language processing applications. However, maximization-based decoding methods (e.g., beam search) of neural language models often lead to degenerate solutions---the generated text is unnatural and contains undesirable repetitions. Existing approaches introduce sto...	Accept	All four reviewers sided to accept the paper, as the proposed contrastive search approach to mitigating text degeneration problem is simple and effective and has applications to a variety of NLG tasks. Its evaluation is quite comprehensive and includes competitive baselines, human evaluation, and evaluation of both LM/...	val	[ "vhGXz0_eBAx", "1brnWHQRnZ3", "geUDHasYjwb", "vpNH_k-4He", "yVgpdBO1sT4X", "59k677nSXUq", "_a58NwIHW4xV", "bPwRE2FlxNd", "TEl5cd0GTRt", "8o_drRyrpT", "zVIOpvI5KN6", "3YR6VMoUPq5", "2mHZdd0oQ3Z", "T56hkp-qWo", "kdhFQZtIHzs" ]	[ "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for reading our response!", " The response has addressed my major concerns. However, contrastive learning and its findings for NLP are not new. \n\nI decide to raise my rating to 5 -- borderline accept.\n\n", " Thank you for reading our response!", " Thank you for your comprehensive reply and add...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 8, 5, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 4 ]	[ "1brnWHQRnZ3", "yVgpdBO1sT4X", "vpNH_k-4He", "_a58NwIHW4xV", "T56hkp-qWo", "kdhFQZtIHzs", "kdhFQZtIHzs", "2mHZdd0oQ3Z", "2mHZdd0oQ3Z", "3YR6VMoUPq5", "nips_2022_V88BafmH9Pj", "nips_2022_V88BafmH9Pj", "nips_2022_V88BafmH9Pj", "nips_2022_V88BafmH9Pj", "nips_2022_V88BafmH9Pj" ]
nips_2022_Gsbnnc--bnw	Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models	Generative models (e.g., GANs, diffusion models) learn the underlying data distribution in an unsupervised manner. However, many applications of interest require sampling from a particular region of the output space or sampling evenly over a range of characteristics. For efficient sampling in these scenarios, we propos...	Accept	This work concerns a unifying method for repurposing "off the shelf" conditional models in order to define an energy-based model of vectors in the latent space of a pre-trained generative model, for the purpose of controlling synthesis, and a feed-forward approximation using invertible neural networks. The authors pres...	train	[ "hJymahhlX6v", "IwrGC_DBXUt", "rPzdRASZ-dh", "mOb2uXRwbIb", "TTePoXoVJRi", "MAqlyZDBMJg", "RyNqXOwil61", "HL6kcFW84G-", "BR0cJsdNuH8", "F3zpUR7kGCw", "_bhYvOU8pN8", "q0cBDN592SC", "X_hfVOZcQe", "_GN8gxqmk-" ]	[ "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Approximation error\n\nThanks for pointing this out! The approximate error can be measured by $D_{\\text{KL}}(p_{\\theta}(\\boldsymbol{z}) \|\| p(\\boldsymbol{z} \| \\mathcal{C}))$. This KL divergence is defined in Eq. (9). However, it is worth noting that $\\log Z$ is expensive to estimate in practice (recall t...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 6, 6, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 3, 5, 4 ]	[ "rPzdRASZ-dh", "mOb2uXRwbIb", "RyNqXOwil61", "MAqlyZDBMJg", "nips_2022_Gsbnnc--bnw", "_GN8gxqmk-", "X_hfVOZcQe", "q0cBDN592SC", "_bhYvOU8pN8", "nips_2022_Gsbnnc--bnw", "nips_2022_Gsbnnc--bnw", "nips_2022_Gsbnnc--bnw", "nips_2022_Gsbnnc--bnw", "nips_2022_Gsbnnc--bnw" ]
nips_2022_LCWQ8OYsf-O	Polyhistor: Parameter-Efficient Multi-Task Adaptation for Dense Vision Tasks	Adapting large-scale pretrained models to various downstream tasks via fine-tuning is a standard method in machine learning. Recently, parameter-efficient fine-tuning methods have shown promise in adapting a pretrained model to different tasks while training only a few parameters. Despite their success, most existing m...	Accept	The proposed Polyhistor and Polyhistor-Lite for parameter-efficient multi-task adaptation achieves competitive performance gains on dense vision datasets. All reviewers give consistent positive scores. The requested experiments for more backbones, self-supervised backbones and analyses have been accordingly added durin...	train	[ "4q58QxRTGT", "0Zc2CCLW99fO", "VqN8Z0RMQ6a", "pFuS339hGX6", "Mv5uZT4Esjf", "_rAU6gSeBy3", "xMsjF5Jfm7v", "h2uf4ti5i6v", "TKMQ4dd9mtk", "hAYmh8ei0x0", "uNbSqOdBwcY", "l2YQMJZbt90", "xyjO6EvinD7" ]	[ "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for your response. I will keep my score unchanged.", " Thank the authors for the response. \nI have no further questions. After reading the rebuttal and other reviewers' comments, I would like to keep my score at 7. ", " We thank all reviewers for providing constructive thoughtful feedback!\n\nWe a...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 5, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 4 ]	[ "pFuS339hGX6", "_rAU6gSeBy3", "nips_2022_LCWQ8OYsf-O", "Mv5uZT4Esjf", "xyjO6EvinD7", "l2YQMJZbt90", "uNbSqOdBwcY", "TKMQ4dd9mtk", "hAYmh8ei0x0", "nips_2022_LCWQ8OYsf-O", "nips_2022_LCWQ8OYsf-O", "nips_2022_LCWQ8OYsf-O", "nips_2022_LCWQ8OYsf-O" ]
nips_2022_hYa_lseXK8	Model-based Safe Deep Reinforcement Learning via a Constrained Proximal Policy Optimization Algorithm	During initial iterations of training in most Reinforcement Learning (RL) algorithms, agents perform a significant number of random exploratory steps. In the real world, this can limit the practicality of these algorithms as it can lead to potentially dangerous behavior. Hence safe exploration is a critical issue in ap...	Accept	This paper presents Model-based PPO-Lagrangian (MBPPO-Lagrangian) algorithm for safe RL, which reduces epistemic and aleatoric uncertainty with an ensemble of neural networks. The authors experimented the proposed algorithm in safety benchmarks such as Safety Gym: PointGoal1 and CarGoal for which MBPPO-Lagrangian show...	train	[ "uezg7zjUD5", "OPLPi24xKoP", "7lIs5rejBL", "qNsyWuKTHO6", "VsTvJSQChey", "tZ0PHYBZs6h", "H7O4upmToN4", "X827usIJD8X", "RnWxJbUHe65", "Uhqu0DGsDrn", "D0Jy53AC0Uf", "MIaULM1ywB-", "5URMZ7Chmqa" ]	[ "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We thank you for your comments. Your suggested changes will be incorporated.", " Thanks for addressing all my concerns regarding the paper! \n\nI have two more recommendations to improve the paper. I wonder whether showing the standard deviations of graphs in Figure 1 and in Appendix D is possible. Also, it wou...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 5, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 4, 4 ]	[ "OPLPi24xKoP", "RnWxJbUHe65", "tZ0PHYBZs6h", "X827usIJD8X", "nips_2022_hYa_lseXK8", "5URMZ7Chmqa", "MIaULM1ywB-", "D0Jy53AC0Uf", "Uhqu0DGsDrn", "nips_2022_hYa_lseXK8", "nips_2022_hYa_lseXK8", "nips_2022_hYa_lseXK8", "nips_2022_hYa_lseXK8" ]
nips_2022_wO53HILzu65	On the Generalizability and Predictability of Recommender Systems	While other areas of machine learning have seen more and more automation, designing a high-performing recommender system still requires a high level of human effort. Furthermore, recent work has shown that modern recommender system algorithms do not always improve over well-tuned baselines. A natural follow-up question...	Accept	The core idea is to specialize meta-learning approaches to recommender systems. The specialization is done using features on the dataset themselves so is different from usual autoML approaches. Some code is provided allowing easy comparison to a lot of well tuned baselines in the domain. Yet easily reusable it is also ...	train	[ "nwh4otVU_Tb", "3Rb0NxMwFbp", "KVBFGo1Oo9", "e3DXg3wzJ_L", "it-WS0JUk5e", "UYXDGaVQ6YJ", "LGR-xo2P8Uv", "6KZnF42ZDYI", "Bxmi2cLJW72", "JRpUdnQCZKc", "V0dDaPfvgbt", "ppycnMAdaBp", "uS_9dY4zB4a" ]	[ "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for your additional feedback. We agree with your minor comment about giving more details for practitioners leveraging Section 2. We have now updated Section C.2 with concrete examples and more details.\n\nNote that the particular use cases and goals of a practitioner may be very specific (they may be co...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 7, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 4, 3, 4 ]	[ "KVBFGo1Oo9", "6KZnF42ZDYI", "it-WS0JUk5e", "Bxmi2cLJW72", "uS_9dY4zB4a", "ppycnMAdaBp", "V0dDaPfvgbt", "JRpUdnQCZKc", "nips_2022_wO53HILzu65", "nips_2022_wO53HILzu65", "nips_2022_wO53HILzu65", "nips_2022_wO53HILzu65", "nips_2022_wO53HILzu65" ]
nips_2022_mMT8bhVBoUa	Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning	We develop a framework for generalized variational inference in infinite-dimensional function spaces and use it to construct a method termed Gaussian Wasserstein inference (GWI). GWI leverages the Wasserstein distance between Gaussian measures on the Hilbert space of square-integrable functions in order to determine a ...	Accept	Technically solid paper that introduces and benchmarks a novel inference framework, with application to inference in GPs. All reviewers recommend to accept, after a decent amount of discussion in which reviewers raised their scores in response to a fairly significant round of updates to the manuscript itself. Recommend...	test	[ "Nm8NRsL2A9v", "1O8Nr77q73-", "N5NVHOc0eyJ", "NhBLJ7z0tg7", "-1kh2llWtte", "flhtJXI4NEN", "_14PmfOKPYE", "d5sPuG_X0k", "59QwKQ5fne", "b74DgukvHAA" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the rebuttal, for answering my questions and for the additional figure. I stand with my previous score, that is I would like to see this paper accepted. ", " I thank the authors for their detailed response. Changes made to address the motivation and model comparisons will substantially improve the ma...	[ -1, -1, -1, -1, -1, -1, -1, 7, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, 4, 4, 4 ]	[ "-1kh2llWtte", "_14PmfOKPYE", "flhtJXI4NEN", "nips_2022_mMT8bhVBoUa", "b74DgukvHAA", "59QwKQ5fne", "d5sPuG_X0k", "nips_2022_mMT8bhVBoUa", "nips_2022_mMT8bhVBoUa", "nips_2022_mMT8bhVBoUa" ]
nips_2022_zuL5OYIBgcV	Non-deep Networks	Latency is of utmost importance in safety-critical systems. In neural networks, lowest theoretical latency is dependent on the depth of the network. This begs the question -- is it possible to build high-performing ``non-deep" neural networks? We show that it is. To do so, we use parallel subnetworks instead of stackin...	Accept	This work considers the task of training state-of-the-art CNNs with limited depth. The benefits considered in this work are related to the potential parallelization which is induced by depth reduction. This paper generated a fair bit of discussion with the reviewers about the motivations and the basic thesis. The autho...	val	[ "q7W43nrhK0t", "OBBlOppRHD8", "5VLOyDT8buX", "w9GscWn15mJ", "Uky-tUI00K", "IK_rou7anBQ", "NYDQaSIHDd9", "AiZrWvEpgrOT", "2AuPYWuWOEM", "eaJMbkiEalA", "D3qntmYPHplx", "a61N5woR6NZ", "BQxZA8Ul4b1", "Z8TYkIwQoB2", "uZ7Bkbtdf_7", "P3d_IJLpbLD", "43AI4ktSBQU", "MWlH6RGrDKf", "p6oduJ1L...	[ "author", "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_re...	[ " We believe that the reviewer is missing the point that as we have hardware with more cores, depth will increasingly become an important and limiting factor as there is no way to circumvent depth (or number of sequential steps). \n\nAlso, we pointed out that the differences caused in latency by large and small dep...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 4, 7, 7, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 4, 5 ]	[ "5VLOyDT8buX", "w9GscWn15mJ", "Uky-tUI00K", "NYDQaSIHDd9", "AiZrWvEpgrOT", "2JNlxK-qRYw", "a61N5woR6NZ", "BQxZA8Ul4b1", "2JNlxK-qRYw", "p6oduJ1LbbH", "MWlH6RGrDKf", "BQxZA8Ul4b1", "43AI4ktSBQU", "P3d_IJLpbLD", "nips_2022_zuL5OYIBgcV", "nips_2022_zuL5OYIBgcV", "nips_2022_zuL5OYIBgcV",...
nips_2022_YpyGV_i8Z_J	Private Estimation with Public Data	We initiate the study of differentially private (DP) estimation with access to a small amount of public data. For private estimation of $d$-dimensional Gaussians, we assume that the public data comes from a Gaussian that may have vanishing similarity in total variation distance with the underlying Gaussian of the priva...	Accept	This paper studies private estimation with a small amount of public data. The idea is that the small public dataset may allow for significantly stronger positive results (e.g., in terms of sample complexity of private data). The authors study two fundamental settings in this direction -- estimating a Gaussian and a Gau...	train	[ "zkhfDLCiy9N", "Rx_OO_Vxe28P", "XhNmPwNF4Nb", "jJsn9o6-OMo", "cY4G7gWM2Qk", "h8QHIRStJ4j", "anp0uJjZZ2O", "whVRWHRWn06", "_JQKTqJsO6U", "WTalcKPar82", "XSKys1JaYGQ" ]	[ "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank the authors for the thoughtful response. The example you gave helps to clarify my question about the relation to $(\\epsilon, \\delta)$-DP, which is my main concern. Therefore, I'm willing to raise my score.", " A proof-of-concept numerical result: \nAlthough we position our work as theoretical, sinc...	[ -1, -1, -1, -1, -1, -1, -1, -1, 4, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 3 ]	[ "cY4G7gWM2Qk", "h8QHIRStJ4j", "XSKys1JaYGQ", "cY4G7gWM2Qk", "WTalcKPar82", "anp0uJjZZ2O", "whVRWHRWn06", "_JQKTqJsO6U", "nips_2022_YpyGV_i8Z_J", "nips_2022_YpyGV_i8Z_J", "nips_2022_YpyGV_i8Z_J" ]
nips_2022_ptUZl8xDMMN	Graph Scattering beyond Wavelet Shackles	This work develops a flexible and mathematically sound framework for the design and analysis of graph scattering networks with variable branching ratios and generic functional calculus filters. Spectrally-agnostic stability guarantees for node- and graph-level perturbations are derived; the vertex-set non-preserving ca...	Accept	In the discussion, we reached a clear consensus that this paper is interesting for the NeurIPS community and should be accepted. The author's rebuttal and subsequent discussion were very useful and we are looking forward to the final version of the paper with the promised improvements implemented.	train	[ "H5sJBYUSuTq", "xlMie1xPK3H", "kQMVxsctndp2", "my1BXEbD3Dl", "Q0E4qKk6V6d", "1ruWgbUT4SU", "QcRPprNnWKK", "sDyns08qrUA", "KVs3xoipRh9", "k6Mqa_nwFS-K", "xplFjj40VcD", "m0PxVrT73Ok", "OM4UnIjUQIM", "7AAdlmclehi" ]	[ "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " It was a pleasure implementing suggestions and providing answers and explanations for questions!", " I thank the authors for their very detailed rebuttal.\n\nI am not going to go over each bullet point again, but I am quite satisfied with the changes provided; especially in section 3 and after each theorem, the...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 3 ]	[ "xlMie1xPK3H", "sDyns08qrUA", "my1BXEbD3Dl", "Q0E4qKk6V6d", "1ruWgbUT4SU", "QcRPprNnWKK", "OM4UnIjUQIM", "KVs3xoipRh9", "k6Mqa_nwFS-K", "7AAdlmclehi", "m0PxVrT73Ok", "nips_2022_ptUZl8xDMMN", "nips_2022_ptUZl8xDMMN", "nips_2022_ptUZl8xDMMN" ]
nips_2022__r8pCrHwq39	PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points	Traditional temporal action detection (TAD) usually handles untrimmed videos with small number of action instances from a single label (e.g., ActivityNet, THUMOS). However, this setting might be unrealistic as different classes of actions often co-occur in practice. In this paper, we focus on the task of multi-label te...	Accept	This paper considers the problem of detecting temporal activities in videos which contain multiple co-occurring activities of different labels. It is an important problem that arises in many computer vision tasks. The paper is generally well written. Specifically, using learnable query points to select representative f...	train	[ "GwFlpRTtCAa", "sLxxsjWiggZ", "95r86oB2TS", "BDByOkCCLZq", "qSRhg8oT7Wj", "g9IpSWVoX7", "SNZ34LpXgU8", "e-pmQrvBxaJ", "NjDMGGS43Kx", "sT52aQ_t4QM", "ki1tlv5P7l", "BzOSwbiteML", "qwDbSbC0buz", "Zf9ih2zCrer", "o8vOZSqT5D" ]	[ "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " > What is the difference between the method proposed in this paper and [2,4], which the author does not seem to mention?\n\nAs we stated in Line 93 of the revised paper and in the first response, [2] and [4] all use points to represent object tracks or spatiotemporal action tracks, with a focus on representing t...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 7, 8 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 5, 4 ]	[ "sLxxsjWiggZ", "SNZ34LpXgU8", "qwDbSbC0buz", "BzOSwbiteML", "nips_2022__r8pCrHwq39", "nips_2022__r8pCrHwq39", "BzOSwbiteML", "qwDbSbC0buz", "qwDbSbC0buz", "Zf9ih2zCrer", "o8vOZSqT5D", "nips_2022__r8pCrHwq39", "nips_2022__r8pCrHwq39", "nips_2022__r8pCrHwq39", "nips_2022__r8pCrHwq39" ]
nips_2022_c63eTNYh9Y	New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma	We prove new lower bounds for statistical estimation tasks under the constraint of $(\varepsilon,\delta)$-differential privacy. First, we provide tight lower bounds for private covariance estimation of Gaussian distributions. We show that estimating the covariance matrix in Frobenius norm requires $\Omega(d^2)$ samples...	Accept	This paper establishes improved and near-optimal lower bounds for private statistical estimation, specifically for private covariance estimation of a Gaussian and heavy-tailed mean estimation. The first result leverages a novel technical result, proved in this paper: a generalization of the fingerprint lemma (Bun, Stei...	train	[ "sGjjfm3_Ioi", "UFrIN6aTcVNy", "95BLqa0FgLe", "Sy3jcu-g_h1a", "hHDlRD3wACM", "WDKyCJoDL-", "xHVThIbryo4", "uPt88MTYOrZ", "fVJQQYxkV2N1", "WtwOtppAaJT", "w7nsNcnudux", "rDomioTuPax" ]	[ "official_reviewer", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks to the authors for addressing my questions. I have no other questions or concerns for now.", " >I understand the challenges you mentioned, and I have no doubt that your extension of the FP lemma to exponential families is completely non-trivial. Yet, you cannot ignore the fact that the structure of the p...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 3, 3 ]	[ "fVJQQYxkV2N1", "Sy3jcu-g_h1a", "xHVThIbryo4", "uPt88MTYOrZ", "WDKyCJoDL-", "WtwOtppAaJT", "uPt88MTYOrZ", "w7nsNcnudux", "rDomioTuPax", "nips_2022_c63eTNYh9Y", "nips_2022_c63eTNYh9Y", "nips_2022_c63eTNYh9Y" ]
nips_2022_AezHeiz7eF5	Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources	Branched Optimal Transport (BOT) is a generalization of optimal transport in which transportation costs along an edge are subadditive. This subadditivity models an increase in transport efficiency when shipping mass along the same route, favoring branched transportation networks. We here study the NP-hard optimization ...	Accept	The paper presents novel structural and algorithmic results for solving the branched optimal transport problem. In the problem, flow is to be routed from sources to sinks (terminals) in the plane with the possibility of adding non-terminal intermediate nodes. The flow cost on each edge is proportional to the distance b...	train	[ "3pMPlvkRFwe", "ylPh2gi6xn", "KC-TzCy628c", "GZ5pJnsRepz", "nKXWP8jVdojf", "enb4P-hXN5k6", "rFa9Tc-3Nl3", "2tb0IH8aOqT", "5rUZtcxpnD", "s4mT_ASaojb", "SG5LvrbfGKi", "ONC5PZ5g9L", "XMmavrpH0Hu", "JmRxS9U7AcL", "eGSHJG5gccD", "mpUUZQmbDx", "jQqo_E7N6go", "pLi6wTF0b0S" ]	[ "official_reviewer", "official_reviewer", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_rev...	[ " I am satisfied with the response to my review. So I can keep the score as it is.", " I see, thank you for the quick reply.", " Thank you for acknowledging our rebuttal. \nWLOG, the OT solution can be assumed to be acyclic [2]. As such, it provides a valid input topology for our greedy optimization (Alg. 3), ...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 5, 4, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 3, 3, 4 ]	[ "SG5LvrbfGKi", "KC-TzCy628c", "enb4P-hXN5k6", "s4mT_ASaojb", "XMmavrpH0Hu", "ONC5PZ5g9L", "2tb0IH8aOqT", "pLi6wTF0b0S", "jQqo_E7N6go", "mpUUZQmbDx", "eGSHJG5gccD", "JmRxS9U7AcL", "JmRxS9U7AcL", "nips_2022_AezHeiz7eF5", "nips_2022_AezHeiz7eF5", "nips_2022_AezHeiz7eF5", "nips_2022_AezH...
nips_2022_cy1TKLRAEML	Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network?	The Physics-Informed Neural Network (PINN) approach is a new and promising way to solve partial differential equations using deep learning. The $L^2$ Physics-Informed Loss is the de-facto standard in training Physics-Informed Neural Networks. In this paper, we challenge this common practice by investigating the relatio...	Accept	The reviewers reached a consensus that this paper meets the bar for being accepted at NeuRIPS, and therefore the AC recommends acceptance. Please refers to the reviews and author's responses for reviewers' opinion on the strength and weakness of the paper.	train	[ "lzKQ7ALCOtT", "qklb0Gkp8xD", "xfRTtnQ-uCp", "Nm1GEpESFoF", "kcZC1KDo9yI", "ekVW-eJqusS", "wvT6LIwTqTT8", "Zkqe2E3wDw_", "4kfqLYrhs6-", "5rkZpSq4tFA", "gDdT72sqm7p", "-v0u8h9LLck", "CAEN1eG69eu", "yIgmk8k0DJ", "1WLC2q3EYV_", "w5Wcc7psQBQ", "DTrMs5iM7Mq" ]	[ "author", "official_reviewer", "author", "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you very much for your re-evaluation and rating update. We will include the relevant discussions on Sobolev norms and $L^p$ norms in the next version of our paper.", " Thanks for the explanation, I suggest making some of these more concrete in the paper. Meanwhile, I have updated my score.", " Thanks fo...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 6, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 3, 3 ]	[ "qklb0Gkp8xD", "xfRTtnQ-uCp", "Nm1GEpESFoF", "4kfqLYrhs6-", "nips_2022_cy1TKLRAEML", "wvT6LIwTqTT8", "gDdT72sqm7p", "nips_2022_cy1TKLRAEML", "DTrMs5iM7Mq", "w5Wcc7psQBQ", "1WLC2q3EYV_", "yIgmk8k0DJ", "yIgmk8k0DJ", "nips_2022_cy1TKLRAEML", "nips_2022_cy1TKLRAEML", "nips_2022_cy1TKLRAEML...
nips_2022_3v44ls_4dbg	Learning Infinite-Horizon Average-Reward Restless Multi-Action Bandits via Index Awareness	We consider the online restless bandits with average-reward and multiple actions, where the state of each arm evolves according to a Markov decision process (MDP), and the reward of pulling an arm depends on both the current state of the corresponding MDP and the action taken. Since finding the optimal control is typi...	Accept	The paper tackles the challenging problem of online learning restless multi armed bandit (RMAB) policies. Among its contributions are the introduction of a new tractable class of RMAP policies to learn over, and tractable learning algorithms, with regret guarantees, along the lines of statistical upper confidence bound...	train	[ "fLVM0zkGHnM", "3Sx6kpsHG3u", "qZf1A87mjqZ", "RX3NqraIWzl", "DA7-oQ-LdFB", "nZIMtYPfoxY", "nS2k9E43qMN", "XtPI5mRP-_", "TZZMxJpIM1r", "6WXLvMqQJuI", "zxIbltrT2SD", "qZD7GWv8EYb", "QsKfAKUhsap", "JWbjjLO-z3C", "s1ptbfK0Jig", "Ap2gFcISm9c" ]	[ "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We thank the reviewer again for clarifying this problem. In the following, we further discuss the reward function in the context of restless multi-armed bandits (RMAB). Note that we consider RMAB, more precisely, R2MAB in this paper, rather than the classical MAB (which is stateless in general), while each arm i...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 5, 7, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 3, 4 ]	[ "3Sx6kpsHG3u", "qZD7GWv8EYb", "6WXLvMqQJuI", "qZD7GWv8EYb", "nZIMtYPfoxY", "nS2k9E43qMN", "XtPI5mRP-_", "Ap2gFcISm9c", "s1ptbfK0Jig", "zxIbltrT2SD", "JWbjjLO-z3C", "QsKfAKUhsap", "nips_2022_3v44ls_4dbg", "nips_2022_3v44ls_4dbg", "nips_2022_3v44ls_4dbg", "nips_2022_3v44ls_4dbg" ]
nips_2022_SbAaNa97bzp	Understanding Robust Learning through the Lens of Representation Similarities	Representation learning, \textit{i.e.} the generation of representations useful for downstream applications, is a task of fundamental importance that underlies much of the success of deep neural networks (DNNs). Recently, \emph{robustness to adversarial examples} has emerged as a desirable property for DNNs, spurring t...	Accept	The authors study representations obtained from image classifiers and contrast the classic training with adversarial training, so-called non-robust and robust networks, respectively. The authors primarily use the CKA metric on CIFAR10 and subsets of ImageNet2012 provide several novel insights on "salient pitfalls" in r...	train	[ "7HpjJ94RyAW", "s1oLM5BKF3", "tRrEM0kYLbr", "_tjIwXoMgsB", "Kh6CK-frVT-", "ZA4rYsKE9Pe", "gGvNlbV4AVR", "CMF8HzGYsUtX", "2BBuLo8GFI3", "nF_rZCebApx", "vklEEhwbbZPp", "lckD6fDNP9F", "PBnLSj1IjTm", "DO13pufvfsy", "3jVYrkflzXU", "zHE4_I-J1kO", "YMUytX7qYxe", "zr6vVvkyLP", "YriM7CZhn...	[ "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_re...	[ " In light of the authors' willingness to sufficiently guard the reach of the claims made and clarify the wording, I've updated my score.", " We thank the reviewer for engaging with our rebuttal. \n\nIn the literature, the notion of adversarial examples is commonly associated with pixel-wise perturbation-based ad...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 4, 6, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 4, 4, 4 ]	[ "s1oLM5BKF3", "_tjIwXoMgsB", "YMUytX7qYxe", "vklEEhwbbZPp", "2BBuLo8GFI3", "3jVYrkflzXU", "CMF8HzGYsUtX", "zr6vVvkyLP", "nF_rZCebApx", "YriM7CZhnoC", "TOno0nETe5x", "nips_2022_SbAaNa97bzp", "YMUytX7qYxe", "YMUytX7qYxe", "zHE4_I-J1kO", "nips_2022_SbAaNa97bzp", "nips_2022_SbAaNa97bzp",...
nips_2022_W-Z8n9HrWn0	Why Do Artificially Generated Data Help Adversarial Robustness	In the adversarial training framework of \cite{carmon2019unlabeled,gowal2021improving}, people use generated/real unlabeled data with pseudolabels to improve adversarial robustness. We provide statistical insights to explain why the artificially generated data improve adversarial training. In particular, we study how t...	Accept	The recommendation is based on the reviewers' comments, the area chair's personal evaluation, and the post-rebuttal discussion. This paper studies how synthetic data can be useful for improving adversarial robustness. All reviewers find the results convincing and valuable. The authors' rebuttal has successfully addre...	train	[ "BS-0NgHtECu", "4HYQyArU4S5", "sECGNQXlE5L", "ECE-pvfKVMb", "H1h5v2CZyUO", "kEqC9TzkKL", "6BiWr1bWh5o", "Ps8T0bJkom1", "2aqzdEwE73R", "DtOwPKU_nlC", "Ms1YIziHEQF", "keBElZRFlzg", "oMS-Gnnv8n" ]	[ "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We would like to thank you again for providing us with such a constructive and encouraging review! We will try to polish our paper to fully emphasize the motivation and make the mathematical formulas easier to understand in the camera-ready version.", " I thank the authors for answering the questions. One of my...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 6, 7, 8 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 3, 2, 4 ]	[ "4HYQyArU4S5", "6BiWr1bWh5o", "ECE-pvfKVMb", "Ps8T0bJkom1", "oMS-Gnnv8n", "keBElZRFlzg", "Ms1YIziHEQF", "DtOwPKU_nlC", "nips_2022_W-Z8n9HrWn0", "nips_2022_W-Z8n9HrWn0", "nips_2022_W-Z8n9HrWn0", "nips_2022_W-Z8n9HrWn0", "nips_2022_W-Z8n9HrWn0" ]
nips_2022_t4vTbQnhM8	A Kernelised Stein Statistic for Assessing Implicit Generative Models	Synthetic data generation has become a key ingredient for training machine learning procedures, addressing tasks such as data augmentation, analysing privacy-sensitive data, or visualising representative samples. Assessing the quality of such synthetic data generators hence has to be addressed. As (deep) generative mo...	Accept	Decision: Accept This paper introduces a non-parametric (NP) Stein operator to allow implicit models to be used in KSD. So this enable the use of KSD for evaluating the performance of implicit models, and the new test statistic shows better test power compared to MMD test. Reviewers commended that the paper writing i...	train	[ "4L5ab32O07v", "uaOTOZ-YAUo", "NzqLVYEGtjd", "UGBL24xUGvK", "gF_o3sNb5ko", "_bkAVmya47X", "74weE6g9PDN", "GExauiBuoKb", "3Mypwq9zmz9U", "ZlNmJ1zqs5", "GQGhqWhRfc_", "eRdRs3IXR5A", "rCZy6idlYox", "82E1jiFV4b" ]	[ "author", "official_reviewer", "author", "official_reviewer", "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you very much for the update. We are very pleased that we have addressed most of your concerns and you now support accepting it!\n", " I appreciate the detailed response from the author. It addresses most of my concerns. I will raise my rating.", " Many thanks for your suggestions. We have amended the t...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 4 ]	[ "uaOTOZ-YAUo", "gF_o3sNb5ko", "UGBL24xUGvK", "GQGhqWhRfc_", "_bkAVmya47X", "ZlNmJ1zqs5", "GExauiBuoKb", "3Mypwq9zmz9U", "rCZy6idlYox", "82E1jiFV4b", "eRdRs3IXR5A", "nips_2022_t4vTbQnhM8", "nips_2022_t4vTbQnhM8", "nips_2022_t4vTbQnhM8" ]
nips_2022_KqI-bX-TfT	Learning Consistency-Aware Unsigned Distance Functions Progressively from Raw Point Clouds	Surface reconstruction for point clouds is an important task in 3D computer vision. Most of the latest methods resolve this problem by learning signed distance functions (SDF) from point clouds, which are limited to reconstructing shapes or scenes with closed surfaces. Some other methods tried to represent shapes or sc...	Accept	All reviewers were clearly in favor of accepting the paper pre-rebuttal. There was limited discussion post-rebuttal. The AC examined the paper, the reviews, and the authors' response and is inclined to accept the paper. The AC encourages the authors to use their extra page to incorporate their responses to the reviewer...	train	[ "HZaG6h1VuPD", "KDWg4f28MgV", "uFSjNbGUTDw", "-aQDpKoJpKY", "id-iRuH1Xx", "YaaYuYVw7XZ", "BU2uxgnOUkc", "HUNByEGv-q", "jWjC69phTF9", "M1MBLwT1_Q0", "AH6hmdOPeRA", "IiSUPkOhvYU", "RNPJu-qVdjz" ]	[ "author", "author", "author", "author", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Dear Reviewer Aixv,\n\nFollowing your questions, we will expand figure captions with detailed descriptions in revision. We would like to know whether you believe we have addressed your concerns, and please let us know if you have any other questions.\n\nThanks for your time,\n\nThe Authors\n\n", " Dear Reviewer...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 6, 8, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 4, 3 ]	[ "jWjC69phTF9", "YaaYuYVw7XZ", "BU2uxgnOUkc", "HUNByEGv-q", "nips_2022_KqI-bX-TfT", "IiSUPkOhvYU", "AH6hmdOPeRA", "M1MBLwT1_Q0", "RNPJu-qVdjz", "nips_2022_KqI-bX-TfT", "nips_2022_KqI-bX-TfT", "nips_2022_KqI-bX-TfT", "nips_2022_KqI-bX-TfT" ]
nips_2022_LT6-Mxgb3QB	Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration $\&$ Planning	We study the problem of episodic reinforcement learning in continuous state-action spaces with unknown rewards and transitions. Specifically, we consider the setting where the rewards and transitions are modeled using parametric bilinear exponential families. We propose an algorithm, $\texttt{BEF-RLSVI}$, that a) uses ...	Reject	The paper presents a tractable algorithm for bilinear exponential MDP with regret bound that improves from the best known result and achieves \sqft{d^3 HK} regret. The result appears to be correct with strong technical analysis. Reviewers and ACs appreciate merits of the analysis for this specific problem class. Howev...	train	[ "gSU_whVX3IP", "05mCyko5nt", "W6NMI07SZqA", "N4f5exetHrt", "Wa2tf89kZB0", "kDRkCg5obHm", "DLFltiRkjs6", "BwOluoXS-ZE0", "vCZz2abGu9I", "_96fsWUtt4S", "NikBNkZ4js1", "3a-r5Bkyvd-", "VMP-NKkz3GL", "bEH77796apX", "4TNrI0w4eoM", "8ZqaaRfW-ny", "TTUxCLQMBjD" ]	[ "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the clarifications! I encourage the authors to include these details in the paper. \n\nI don't have any further questions, and I will adjust my rating to 6 accordingly. I hope our conversation can help you revise the paper.", " Thank you for your helpful input and for engaging with our rebuttal.\n\nR...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 3 ]	[ "W6NMI07SZqA", "N4f5exetHrt", "kDRkCg5obHm", "DLFltiRkjs6", "NikBNkZ4js1", "BwOluoXS-ZE0", "_96fsWUtt4S", "vCZz2abGu9I", "3a-r5Bkyvd-", "bEH77796apX", "TTUxCLQMBjD", "8ZqaaRfW-ny", "4TNrI0w4eoM", "nips_2022_LT6-Mxgb3QB", "nips_2022_LT6-Mxgb3QB", "nips_2022_LT6-Mxgb3QB", "nips_2022_LT...
nips_2022_3I8VTXMhuPx	Hiding Images in Deep Probabilistic Models	Data hiding with deep neural networks (DNNs) has experienced impressive successes in recent years. A prevailing scheme is to train an autoencoder, consisting of an encoding network to embed (or transform) secret messages in (or into) a carrier, and a decoding network to extract the hidden messages. This scheme may suff...	Accept	This paper studies a novel variation of image steganography. The proposed approach is different from prior work (mostly building on autoencoders) and uses a GAN and hide a secret image in one particular location of the learned distribution. The central idea of the paper seems novel and interesting. The reviewers raise...	test	[ "5R1L5wgYI8", "NbbXjgChTuU", "8yszKUkpN6g", "lZQE79MVV4J", "7DRMwIJzsBM", "PsMmUYcWP5", "heUQ5AdGxY" ]	[ "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for appreciating our work. The summary of the current paper is indeed thorough and accurate. \n\n1. We thank the reviewer to recognize the ability of the proposed method to hide multiple images for different receivers as a significant advantage over previous methods, despite that we choose to down-weight t...	[ -1, -1, -1, -1, 3, 5, 7 ]	[ -1, -1, -1, -1, 4, 2, 3 ]	[ "heUQ5AdGxY", "PsMmUYcWP5", "lZQE79MVV4J", "7DRMwIJzsBM", "nips_2022_3I8VTXMhuPx", "nips_2022_3I8VTXMhuPx", "nips_2022_3I8VTXMhuPx" ]
nips_2022_iMK2LP0AogI	CUP: Critic-Guided Policy Reuse	The ability to reuse previous policies is an important aspect of human intelligence. To achieve efficient policy reuse, a Deep Reinforcement Learning (DRL) agent needs to decide when to reuse and which source policies to reuse. Previous methods solve this problem by introducing extra components to the underlying algori...	Accept	The paper proposes a method for how to leverage a list of pretrained policies for learning a new task, by picking the guidance policy through maximal one-step policy improvement evaluated with the learned critic. Contribution is simple, but writing, theories, and experiments/ablation studies are clean and easy to foll...	train	[ "EKEW60cOsiC", "E29WE-DjOTn", "TMhaXisxxt", "9dVEW3J2d9G", "-2KfdDbm45", "fVvEsE9PXBI", "IZNfFjr3Ld", "ehkzH_bgZt", "8AfYOG1X6mO", "TldoHwZ1Q_F", "N0fNiYKluSt", "Yfi2-v1shYi", "C7tW11TiH-8", "ys65rbSDyUe", "G4UZx3ZSwqE", "TXPjdnK2YlP", "gfo-IuBEJzb", "EUDOBQDIv-f", "aLhzSxG0PV9",...	[ "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_r...	[ " Thank you for the detailed response! The additional clarification and experiments address my problems. ", " Thank you for the encouraging response! We are glad that our response addresses your concerns. We are grateful for your valuable questions and suggestions, which help improve the paper.", " Hi Authors,\...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 5, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 5 ]	[ "TXPjdnK2YlP", "TMhaXisxxt", "9dVEW3J2d9G", "aLhzSxG0PV9", "EUDOBQDIv-f", "gfo-IuBEJzb", "ehkzH_bgZt", "8AfYOG1X6mO", "TldoHwZ1Q_F", "Yfi2-v1shYi", "Yfi2-v1shYi", "NVTR0evMDc", "ys65rbSDyUe", "aLhzSxG0PV9", "EUDOBQDIv-f", "gfo-IuBEJzb", "nips_2022_iMK2LP0AogI", "nips_2022_iMK2LP0Ao...
nips_2022_NJr8GBsyTF0	Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning	We generalise the problem of reward modelling (RM) for reinforcement learning (RL) to handle non-Markovian rewards. Existing work assumes that human evaluators observe each step in a trajectory independently when providing feedback on agent behaviour. In this work, we remove this assumption, extending RM to capture tem...	Accept	The reviewers have agreed on many points (at least after some help from the author's explanations and changes in the rebuttal): the problem formulation is interesting (in particular as it relates to evolving human preferences, but also in the practical experimental cases), the writing is clear and the technical solutio...	train	[ "Zi7qVm-ykC", "IWpq9O-mJ1Z", "PbJ_wbnbyq", "Tqp0RaGVCIv", "yNg18aPob7i", "6jiubyZfqiE", "jjiZ_Gnt75_7", "MflSMAJMBSne", "aCvRYQHqBBZ", "L1Oyq79128F", "Ai5hwij5M92", "77Z6KqURxA6", "YUGrHi0Adpr", "K3dZT8Ce91d", "sOYehp1fl7N", "swivzwOOSo4" ]	[ "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you again for your comments. Please see our recently submitted final revision, which completes both sets of changes that we laid out in our General Rebuttal. ", " We have now submitted our final revision of the paper. Below we detail the overall changes between this final version and the original vers...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 4, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4 ]	[ "jjiZ_Gnt75_7", "nips_2022_NJr8GBsyTF0", "nips_2022_NJr8GBsyTF0", "6jiubyZfqiE", "nips_2022_NJr8GBsyTF0", "Ai5hwij5M92", "77Z6KqURxA6", "swivzwOOSo4", "L1Oyq79128F", "sOYehp1fl7N", "K3dZT8Ce91d", "YUGrHi0Adpr", "nips_2022_NJr8GBsyTF0", "nips_2022_NJr8GBsyTF0", "nips_2022_NJr8GBsyTF0", ...
nips_2022_S0TR0W63NKl	Generalization Bounds for Estimating Causal Effects of Continuous Treatments	We focus on estimating causal effects of continuous treatments (e.g., dosage in medicine), also known as dose-response function. Existing methods in causal inference for continuous treatments using neural networks are effective and to some extent reduce selection bias, which is introduced by non-randomized treatments a...	Accept	The authors propose theory and an algorithm for estimating average dose-response functions (ADRF) from observational data under assumptions of unconfoundedness and overlap. The approach extends theory and methodology from primarily the work in [13] where neural networks and integral probability metrics are used to lear...	train	[ "aorA3_fWDdq", "WqZdKQ8XfJ0", "3cr2E7kBRd8", "SpelEwEVbvI", "pZUrD31s2Qn", "YFyqweQuN6Q", "FjmX8MpRG4", "r80uf5A-GUx", "BzPmM7M-B_9", "J9XIgKd3t3e", "1KZWUEoak6w", "diL2WbwHVVw", "ypUAHmAHziN", "_Hb8Sp_0g1A" ]	[ "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for clarifying my concerns. I will be maintaining my score.", " I thank the authors for the detailed answers. I re-read the paper and, while the author responses make the context and technical contribution more clear, I believe it should not take a 2 page response to get the main points across. All of...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 5, 3, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 3, 4 ]	[ "YFyqweQuN6Q", "3cr2E7kBRd8", "ypUAHmAHziN", "pZUrD31s2Qn", "J9XIgKd3t3e", "_Hb8Sp_0g1A", "r80uf5A-GUx", "ypUAHmAHziN", "diL2WbwHVVw", "1KZWUEoak6w", "nips_2022_S0TR0W63NKl", "nips_2022_S0TR0W63NKl", "nips_2022_S0TR0W63NKl", "nips_2022_S0TR0W63NKl" ]
nips_2022_bGo0A4bJBc	Cost-Sensitive Self-Training for Optimizing Non-Decomposable Metrics	Self-training based semi-supervised learning algorithms have enabled the learning of highly accurate deep neural networks, using only a fraction of labeled data. However, the majority of work on self-training has focused on the objective of improving accuracy whereas practical machine learning systems can have complex ...	Accept	The paper received two negative scores 3/4 (another is 8 with high confidence 5) and the main critcism is that the writing is vague especially for the topic of the paper may not be very popular to the community. The authors have made good efforts in improving their presentation and they also provide additional clarific...	train	[ "m58lNK34L8", "Agx6GkyR87", "YqnBokNTY20", "Kqw2AoQawWT", "tmDlfdNTkhdQ", "yXj-01U1UD4m", "H1IyC_9k6Rfl", "xXOK7Ha_3d", "eTZUKEhd835", "TWq2WAOc8g4", "Y8VcHju7DXP", "xV5DLIaey2w" ]	[ "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the answers. I think the paper should have been submitted in a readable form in the first submission. \nI want to wish success in the next submission with a better version of the paper that should be further improved both with respect to the writing clarity and the quality of the experiments. Specifica...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 8 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 3, 5 ]	[ "Kqw2AoQawWT", "nips_2022_bGo0A4bJBc", "Y8VcHju7DXP", "tmDlfdNTkhdQ", "yXj-01U1UD4m", "Y8VcHju7DXP", "nips_2022_bGo0A4bJBc", "TWq2WAOc8g4", "xV5DLIaey2w", "nips_2022_bGo0A4bJBc", "nips_2022_bGo0A4bJBc", "nips_2022_bGo0A4bJBc" ]
nips_2022_jJwy2kcBYv	SPD: Synergy Pattern Diversifying Oriented Unsupervised Multi-agent Reinforcement Learning	Reinforcement learning typically relies heavily on a well-designed reward signal, which gets more challenging in cooperative multi-agent reinforcement learning. Alternatively, unsupervised reinforcement learning (URL) has delivered on its promise in the recent past to learn useful skills and explore the environment wit...	Accept	Reviewers appreciated the paper's contribution of a novel method for unsupervised skill learning in MARL. While the scores were borderline, reviewers are mostly in favor of acceptance, therefore I recommend acceptance as well. Additional baselines and environments added during the rebuttal phase were important consider...	val	[ "gwAfZooa16Q", "Su1Lsi1b30H", "X9cREdxmceH", "KZZGdHVRcU-", "L4xfaa5fP_4", "6pqtNe-txPAQ", "nOk7X9HSMHc", "Cn5heZ-JTC", "ecy9dEexydm", "SFarmKvz90", "Zp_EbVpYHIV", "u28Klj0ZQE", "41ubI2mpq4w", "fSIreI3VbMa" ]	[ "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for the rebuttal. \nMy unclear points are clarified. \nAlthough I have less confidence in my understanding, I raised my score. \n", " We sincerely appreciate all reviewers for their time and efforts in evaluating our paper, as well as their detailed comments and suggestions.\n\nWe hope that our respon...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 7, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 3, 4 ]	[ "ecy9dEexydm", "nips_2022_jJwy2kcBYv", "KZZGdHVRcU-", "6pqtNe-txPAQ", "u28Klj0ZQE", "u28Klj0ZQE", "u28Klj0ZQE", "fSIreI3VbMa", "41ubI2mpq4w", "Zp_EbVpYHIV", "nips_2022_jJwy2kcBYv", "nips_2022_jJwy2kcBYv", "nips_2022_jJwy2kcBYv", "nips_2022_jJwy2kcBYv" ]
nips_2022_TTM7iEFOTzJ	EpiGRAF: Rethinking training of 3D GANs	A recent trend in generative modeling is building 3D-aware generators from 2D image collections. To induce the 3D bias, such models typically rely on volumetric rendering, which is expensive to employ at high resolutions. Over the past months, more than ten works have addressed this scaling issue by training a separate...	Accept	The reviewers found the method simple and effective and considered it a contribution of interest to the community. Claims are well supported by experiments and design choices have been validated. The paper is well written. Furthermore, the authors provided highly detailed responses to all questions by reviewers, which ...	test	[ "BKk-tLzFYjW", "V_SKhiggND7", "23Mw4KbVBb", "m7GqTCwVsLX", "VtedKmDiaHS", "pZ3kd-9Def0", "oIErTxvlPPx", "pjn9FRqUFs", "Nxw2zXZne5p", "XI6If5Nn5Dj", "OgMjOlPbp1Q", "Zw6wdfSO3dZ", "b8aDZVqbH9g", "O02Rrg9lCPS", "_JwSNEfncHZ", "HoykHFPUhYJ", "y2zuhLFAsQb" ]	[ "official_reviewer", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the reply. I would encourage the authors to add discussion on sampling strategy in the paper. The rebuttal answers my questions and I would like to keep the original rating.", " Dear Reviewer, we are very thankful for your feedback which helped us to improve several important parts of our work. And ...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 5, 6, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 3, 4, 3 ]	[ "Nxw2zXZne5p", "_JwSNEfncHZ", "Zw6wdfSO3dZ", "oIErTxvlPPx", "nips_2022_TTM7iEFOTzJ", "y2zuhLFAsQb", "y2zuhLFAsQb", "HoykHFPUhYJ", "HoykHFPUhYJ", "_JwSNEfncHZ", "_JwSNEfncHZ", "O02Rrg9lCPS", "nips_2022_TTM7iEFOTzJ", "nips_2022_TTM7iEFOTzJ", "nips_2022_TTM7iEFOTzJ", "nips_2022_TTM7iEFOTz...
nips_2022_oprTuM8F3dt	Coordinates Are NOT Lonely - Codebook Prior Helps Implicit Neural 3D representations	Implicit neural 3D representation has achieved impressive results in surface or scene reconstruction and novel view synthesis, which typically uses the coordinate-based multi-layer perceptrons (MLPs) to learn a continuous scene representation. However, existing approaches, such as Neural Radiance Field (NeRF) and its v...	Accept	This paper focuses on improving the training efficiency of coordinate based representations by reducing the number of camera views needed during training. To accomplish this, the authors proposed a codebook attention module and a coordinate attention module to inject prior knowledge into implicit representations. The i...	train	[ "Aiv3ZATEBCQ", "p0hiBHjQKxn", "DieeZHR0UCi", "UcLwAW8NYI", "MsJ9KCF5rKt", "mGXGF9ItiLb", "EFj9gyTTp4C", "5fW-EVnC9cB", "ttr_7Z9pJUS", "jXaBqHcJxwT", "1wzO1UnyoE", "Nz449rURjg", "_gYTfxpMaiS", "QP90EEcZ3Gs", "F28JDvevpA", "-Wn3zThW2Q5", "QkfhKWvtpU3", "Yjz6V0xYRjL" ]	[ "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We appreciate your valuable and insightful comments. We feel glad about your generally favorable assessment of our methodology. Additional evaluation/ablation and corresponding explanations will be included in the final version.", " We appreciate your valuable and insightful comments. We feel glad about your ge...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 5, 5, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 4, 3 ]	[ "DieeZHR0UCi", "UcLwAW8NYI", "EFj9gyTTp4C", "Nz449rURjg", "Yjz6V0xYRjL", "Yjz6V0xYRjL", "Yjz6V0xYRjL", "QkfhKWvtpU3", "QkfhKWvtpU3", "F28JDvevpA", "F28JDvevpA", "F28JDvevpA", "-Wn3zThW2Q5", "-Wn3zThW2Q5", "nips_2022_oprTuM8F3dt", "nips_2022_oprTuM8F3dt", "nips_2022_oprTuM8F3dt", "n...
nips_2022_VQ9fogN1q6e	Factored Adaptation for Non-Stationary Reinforcement Learning	Dealing with non-stationarity in environments (e.g., in the transition dynamics) and objectives (e.g., in the reward functions) is a challenging problem that is crucial in real-world applications of reinforcement learning (RL). While most current approaches model the changes as a single shared embedding vector, we leve...	Accept	The paper proposes a factored reinforcement-learning method to deal with non-stationary environments. After reading the authors' rebuttals, the reviewers agree that this paper provides an original and sound contribution that deserves publication. We recommend that the authors modify their paper as reported in their ans...	train	[ "xcSg23kr6NM", "0mKRC1hQsl0", "Ehcp96rw1ze", "EzDD6oQ-XH", "U3oBjH2XblO", "MwgBkh8DbM8", "lFAqUL4udY-", "wuuf0HpmWbS", "6bkaqZcQN1f", "Y8XcoGT81cN", "-FJEsgRPstM", "DpPtziADEBOn", "-F9P9AubNfb", "ciBhEBdS7rJ", "M2ZDbOf1ig", "_Fh1vvXmKHj", "8MHz7rP4k5O", "ld7Pp-S8dXv", "KqoKI-tsuW...	[ "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for your thoughtful review. We will be happy to discuss if you have any other concerns. \n", " We would like to express our sincere thanks for your positive feedback and valuable suggestions. \n- As you suggested in Q4, we have updated a new revision, which includes the ablation studies on the disenta...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 6, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 1, 3, 4 ]	[ "ciBhEBdS7rJ", "lFAqUL4udY-", "U3oBjH2XblO", "MwgBkh8DbM8", "wuuf0HpmWbS", "M2ZDbOf1ig", "-FJEsgRPstM", "6bkaqZcQN1f", "Y8XcoGT81cN", "KqoKI-tsuWC", "DpPtziADEBOn", "-F9P9AubNfb", "qKFJ7CFiX7v", "ld7Pp-S8dXv", "_Fh1vvXmKHj", "8MHz7rP4k5O", "nips_2022_VQ9fogN1q6e", "nips_2022_VQ9fog...
nips_2022_0JV4VVBsK6a	Bringing Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens	Recent action recognition models have achieved impressive results by integrating objects, their locations and interactions. However, obtaining dense structured annotations for each frame is tedious and time-consuming, making these methods expensive to train and less scalable. At the same time, if a small set of annotat...	Accept	This paper proposes StructureViT (SViT), a network architecture to incorporate structured information from images to aid in video tasks. All four reviewers found several aspects of the paper interesting including the ability to use information from just a few images and be beneficial to video tasks. They noted the thor...	train	[ "A73QzbQ0R1s", "muKvD3wjTLA", "CvmHrLhmQY_", "q8_4mD9M4n_", "QX68AJfzMe", "3n4MQLEXpE", "LO0oYv4ZazO", "68RI0YBIKsg", "kApS2-Dt_W-", "RuQZ5MhQPeY", "PedhLFk7Vi6", "QMQ4o7ylOhB", "5N3K6ns-6BW", "RSDYUPuHjdA", "3mJPCPwS_rD", "mzVhFG5mr4I", "0VuCszxw0WQ", "5npGaw841Yb", "WZ-NqvgM93o...	[ "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_...	[ " I thank the authors for thoroughly answering all my concerns. \n\nI am reasonably convinced about the general applicability of their proposed approach to several tasks after their provided additional results.\n", " Thank you for your insightful comments. \n\nIn our method, we model objects and hands with object...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 4, 6, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 5 ]	[ "5N3K6ns-6BW", "q8_4mD9M4n_", "QX68AJfzMe", "mzVhFG5mr4I", "3n4MQLEXpE", "68RI0YBIKsg", "kApS2-Dt_W-", "PedhLFk7Vi6", "WZ-NqvgM93o", "5npGaw841Yb", "QMQ4o7ylOhB", "3CRrZRToGo5", "MdEFKx14pec", "3mJPCPwS_rD", "mzVhFG5mr4I", "0VuCszxw0WQ", "yhZ04PMJsLp", "D5FGdoyTwz", "nips_2022_0J...
nips_2022_NkK4i91VWp	Increasing Confidence in Adversarial Robustness Evaluations	Hundreds of defenses have been proposed to make deep neural networks robust against minimal (adversarial) input perturbations. However, only a handful of these defenses held up their claims because correctly evaluating robustness is extremely challenging: Weak attacks often fail to find adversarial examples even if the...	Accept	This paper proposes a simple yet effective test to identify weak adversarial attacks, and thus weak defense evaluations. Empirical results have revealed insufficiently strong evaluations in 11/13 previous published defenses. To me, the paper studies an important problem and makes a valuable contribution to the active r...	train	[ "i045wtKBTGh", "zZWFWtkquEN", "6-gZlgmLqJ", "rfOaa5-QmAG", "nyfZ5oofUPF", "gRPlxAhjsjC", "ZsAssj5VDPH", "FZ8dNUoAVJh", "hhY4iwoVki", "iaVefuOZdiV", "lbnOfOCSLx9", "F6Af4Ae9kcu", "8aMU-2FqA-M", "kSmArjRvszv" ]	[ "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Dear Reviewer,\n\nThank you for your response and your overall positive assessment of our work! We would be grateful if you could let us know what aspects of the paper would need to be improved so you would consider a higher overall assessment. We will do what we can to address any remaining concerns and thank yo...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 6, 6, 8 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 4, 5 ]	[ "6-gZlgmLqJ", "rfOaa5-QmAG", "FZ8dNUoAVJh", "gRPlxAhjsjC", "nips_2022_NkK4i91VWp", "kSmArjRvszv", "kSmArjRvszv", "8aMU-2FqA-M", "F6Af4Ae9kcu", "lbnOfOCSLx9", "nips_2022_NkK4i91VWp", "nips_2022_NkK4i91VWp", "nips_2022_NkK4i91VWp", "nips_2022_NkK4i91VWp" ]
nips_2022_zbuq101sCNV	TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition	Creation of 3D content by stylization is a promising yet challenging problem in computer vision and graphics research. In this work, we focus on stylizing photorealistic appearance renderings of a given surface mesh of arbitrary topology. Motivated by the recent surge of cross-modal supervision of the Contrastive Langu...	Accept	This paper presents a new CLIP-driven stylization method given an input mesh and text description. Compared to previous works Text2Mesh, the paper introduces a more expressive rendering model based on learnable SVBRDF and normal maps. Many reviewers found the paper easy to follow, the idea promising, and the results v...	train	[ "10muIgpP4mE", "BxNNR6XVdWB", "lIWctFja3-h", "G1UgoRGyigm", "ly1zSatz50P", "5cK29RWgqG4", "vh276Ag4Lki", "hcOMqCZEgMc", "vYAkU0FSxw-", "Q1194HZhOBL", "nxkKXHxut2m", "ZgOJ3FDGlJu", "UHul6mOdKy" ]	[ "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the comments and additional experiments. The authors' response has resolved most of my concerns, especially the explanation of the disentanglement of light and reflectance. On the other hand, I agree with the comments from Review kpuS that the limitations of this method and Text2mesh should be discusse...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 4, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 4, 4 ]	[ "5cK29RWgqG4", "nips_2022_zbuq101sCNV", "G1UgoRGyigm", "vh276Ag4Lki", "UHul6mOdKy", "ZgOJ3FDGlJu", "nxkKXHxut2m", "Q1194HZhOBL", "nips_2022_zbuq101sCNV", "nips_2022_zbuq101sCNV", "nips_2022_zbuq101sCNV", "nips_2022_zbuq101sCNV", "nips_2022_zbuq101sCNV" ]
nips_2022_HIslGib8XD	AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control	Given an unsupervised novelty detection task on a new dataset, how can we automatically select a ''best'' detection model while simultaneously controlling the error rate of the best model? For novelty detection analysis, numerous detectors have been proposed to detect outliers on a new unseen dataset based on a score f...	Accept	The paper proposes a method for finding the best anomaly detector among a set of candidate methods that are all based on constructing a score function. The selection method is based on a leave-one-out estimate. Some theoretical results are presented and proven in the appendix, and in addition, some experiments are repo...	val	[ "MAedsfmaLr0", "66yvH5jbONY", "wSS2B1Io_7Y", "DP33cR5VIt", "qRfNfQ7bMWJ", "mZT4ryOD63w", "DbpdJYK1h_", "luQw6NfemKR", "gvWF0H3OhX3", "v8HMNqIH8-e", "LVyq5tbqOk3", "w4bHLYK4ZA9" ]	[ "author", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " \nDear Reviewer MLPQ,\n\nThank you for providing the insightful comments on the Experiment scale of our AutoMS method and METAOD.\nWe have tried our best to answer your questions piece by piece, to make it clear that why there is no need for our AutoMS method to go through hundreds of datasets. As MetaOD uses...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 4, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 2 ]	[ "LVyq5tbqOk3", "DP33cR5VIt", "qRfNfQ7bMWJ", "mZT4ryOD63w", "DbpdJYK1h_", "w4bHLYK4ZA9", "LVyq5tbqOk3", "v8HMNqIH8-e", "nips_2022_HIslGib8XD", "nips_2022_HIslGib8XD", "nips_2022_HIslGib8XD", "nips_2022_HIslGib8XD" ]
nips_2022_omI5hgwgrsa	Optimal Algorithms for Decentralized Stochastic Variational Inequalities	Variational inequalities are a formalism that includes games, minimization, saddle point, and equilibrium problems as special cases. Methods for variational inequalities are therefore universal approaches for many applied tasks, including machine learning problems. This work concentrates on the decentralized setting, w...	Accept	The paper makes a significant contribution to the literature on distributed SVIs. The results provided are fairly comprehensive -- both lower bounds and algorithms achieving the lower bounds are provided. Hence, the paper is recommended for acceptance.	train	[ "JwOS4uonNR", "5P2CB4zIaUW", "Jxkj6ypJld", "DG57C4ZO-hh", "DokUYpN5e6_", "ZbiyTcwT3aQ", "wguDRuYabqP", "-eFFJZAqKzP", "l8BNoGdn4ju", "zNh2uhLQHoT", "Za3yPrLtt-3", "U3p48Hsw8ef", "IobNwRXCz4b" ]	[ "author", "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We're glad to hear it! Thanks again for the review!", " Thanks for the response. As in my previous review, I think this paper has value, and I still think this paper can be accepted. Variational inequality has more applications than optimization.", " With this message, we would just like to kindly remind Revi...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 7, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 3 ]	[ "5P2CB4zIaUW", "-eFFJZAqKzP", "nips_2022_omI5hgwgrsa", "DokUYpN5e6_", "IobNwRXCz4b", "IobNwRXCz4b", "IobNwRXCz4b", "U3p48Hsw8ef", "Za3yPrLtt-3", "nips_2022_omI5hgwgrsa", "nips_2022_omI5hgwgrsa", "nips_2022_omI5hgwgrsa", "nips_2022_omI5hgwgrsa" ]
nips_2022_9U4gLR_lRP	Logit Margin Matters: Improving Transferable Targeted Adversarial Attack by Logit Calibration	Previous works have extensively studied the transferability of adversarial samples in untargeted black-box scenarios. However, it still remains challenging to craft the targeted adversarial examples with higher transferability than non-targeted ones. Recent studies reveal that the traditional Cross-Entropy (CE) loss fu...	Reject	In this paper, the authors propose novel method to improve transferability of targeted adversarial attacks by enlarging the margin between targeted logit and non-target logits. Experiments on ImageNet with different methods demonstrated the effectiveness of the method. However, as is pointed out by the reviewers that ...	train	[ "04OYiCm6jg", "VacpnSA35Nc", "sT14tZIeoddW", "jNXvtEGBFMIS", "sIAr738LGW9", "OyP0Pw8xB5", "IfQv4z1bM6K", "gLRl60iGOpe", "7eZgZ-rivOg", "eqDmaQ47r91", "IDrIEbjfT7Y", "bNMs61pCbvC", "JcXe9C2n82K" ]	[ "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " I would like to thank the authors for their response and have checked the revised version. I agree with Reviewer WQZv that the change of the current version is falling into a major revision. In particular, I would like to highlight the high overlap between the previous submitted manuscript and the existing work. ...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 6, 5, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 5, 4, 4 ]	[ "7eZgZ-rivOg", "jNXvtEGBFMIS", "nips_2022_9U4gLR_lRP", "sIAr738LGW9", "OyP0Pw8xB5", "JcXe9C2n82K", "bNMs61pCbvC", "IDrIEbjfT7Y", "eqDmaQ47r91", "nips_2022_9U4gLR_lRP", "nips_2022_9U4gLR_lRP", "nips_2022_9U4gLR_lRP", "nips_2022_9U4gLR_lRP" ]
nips_2022_2EQzEE5seF	Adversarially Perturbed Batch Normalization: A Simple Way to Improve Image Recognition	Recently, it has been shown that adversarial training (AT) by injecting adversarial samples can improve the quality of recognition. However, the existing AT methods suffer from the performance degradation on the benign samples, leading to a gap between robustness and generalization. We argue that this gap is caused by ...	Reject	The paper presents a new way of bridging the gap between models’ generalization and robustness, by combining gradients computed on unperturbed BN statistics with gradients computed on perturbed statistics. The main goal is to improve the standard generalization, but the authors should clarify their definition of "robus...	train	[ "RjLNTOrnS7", "kUAUmsa75zZ", "D16-Vn2X-qK", "yI3DIcDWGgb", "XUlT8cWDlgO", "_iUK-AEkbF", "mfNvDcYwESe", "z5zom5iC5d1", "GQufvbUajNF", "BLP-ko1mdm3", "cQ48IUAjIlj", "FsXHRovW6BS" ]	[ "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the rebuttal, however, the responses only address parts of my concerns. I feel grateful that the authors have added the robustness experiments on ImageNet-C, while many experiments (e.g., Mixup on ImageNet, more backbones on ImageNet) are still missing for now. In my opinion, experiments for this paper...	[ -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 3, 4 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 4, 4 ]	[ "kUAUmsa75zZ", "FsXHRovW6BS", "cQ48IUAjIlj", "cQ48IUAjIlj", "BLP-ko1mdm3", "GQufvbUajNF", "GQufvbUajNF", "nips_2022_2EQzEE5seF", "nips_2022_2EQzEE5seF", "nips_2022_2EQzEE5seF", "nips_2022_2EQzEE5seF", "nips_2022_2EQzEE5seF" ]
nips_2022_LEqYZz7cZOI	Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning	Freezing the pre-trained backbone has become a standard paradigm to avoid overfitting in few-shot segmentation. In this paper, we rethink the paradigm and explore a new regime: {\em fine-tuning a small part of parameters in the backbone}. We present a solution to overcome the overfitting problem, leading to better mode...	Accept	This paper presents a solution to overcome the overfitting problem in few-shot segmentation. Specifically, the proposed method decomposes the backbone parameters into three matrices via singular value decomposition (SVD) and fine-tunes only the singular values, while leaving the others frozen. This allows the model to ...	train	[ "V-Ybl7lwE3U", "hynhqWz7QE", "ysHodz71zOR", "fvmbJiLXmq", "rPuWKhqM9c", "bMreHwSKVDP", "aiBEZFA-9al", "9I8ALjDxLQHj", "DLMKVx2Rch6", "8Ni53g-pq-", "yo4vr2ibeUnV", "__bmyGgw4MaL", "cM6Bn11jmJ", "eRAkE_rPPB2", "5JVWvrZiquY", "XzNUL7mU5JS", "OeVQOCQPl2e", "HjLr_IpBVSz", "dXGQryd7iy1...	[ "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_r...	[ " We agree with the reviewer that good performance should be achieved when R=U. The above analysis of 2 and 3 is for random rotation matrix, and does not include the special case of R=U. According to the above results and analysis, we conclude that the choice of R is very important. \n\nFollowing the reviewer's sug...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 7, 7, 8 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 5, 4 ]	[ "fvmbJiLXmq", "cM6Bn11jmJ", "OeVQOCQPl2e", "9I8ALjDxLQHj", "8E_wAQvQjNO", "dXGQryd7iy1", "DLMKVx2Rch6", "8Ni53g-pq-", "yo4vr2ibeUnV", "5JVWvrZiquY", "__bmyGgw4MaL", "eRAkE_rPPB2", "8E_wAQvQjNO", "vCQAVh-_rml", "XzNUL7mU5JS", "XxpRT9q6noL", "HjLr_IpBVSz", "dXGQryd7iy1", "nips_2022...
nips_2022_KCXQ5HoM-fy	Supported Policy Optimization for Offline Reinforcement Learning	Policy constraint methods to offline reinforcement learning (RL) typically utilize parameterization or regularization that constrains the policy to perform actions within the support set of the behavior policy. The elaborative designs of parameterization methods usually intrude into the policy networks, which may bring...	Accept	This work presents an interesting idea of constraining the policy network in offline reinforcement learning (RL) to not only be within the support set but also avoid the out-of-distribution actions effectively unlike the standard behavior policy through behavior regularization. The proposed Supported Policy OpTimiza...	train	[ "iNsk8RUtzV", "63IidCfA4L9", "PpinE77wq0F", "WyvhAnLE_cN", "Z4w8lQIyc2w", "b4M_YuTp0G8", "8Z3fr7-pgvG", "qnYX29-RsnJ", "zYUZN57ZOev", "J9YqTTx39u", "1SZNVnn9tMjx", "4QhzeeRzkMI", "8Xi9NjFlG7d", "Kic2JGjLD98", "9RFg_XsEz2F", "3Wy8C7COq9", "YSlemDntD7o" ]	[ "author", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We'd like to thank you again for your time and efforts in providing a valuable review and carefully judging our feedback. We really enjoy the communication, and it helps us make our paper better.", " Thanks for the detailed response. Most of my concerns are solved. I will increase my score.", " Dear Reviewer,...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 6, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 2, 4 ]	[ "63IidCfA4L9", "PpinE77wq0F", "Kic2JGjLD98", "b4M_YuTp0G8", "J9YqTTx39u", "8Xi9NjFlG7d", "nips_2022_KCXQ5HoM-fy", "YSlemDntD7o", "3Wy8C7COq9", "9RFg_XsEz2F", "4QhzeeRzkMI", "8Xi9NjFlG7d", "Kic2JGjLD98", "nips_2022_KCXQ5HoM-fy", "nips_2022_KCXQ5HoM-fy", "nips_2022_KCXQ5HoM-fy", "nips_...
nips_2022_DhmYYrH_M3m	Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline	Current end-to-end autonomous driving methods either run a controller based on a planned trajectory or perform control prediction directly, which have spanned two separately studied lines of research. Seeing their potential mutual benefits to each other, this paper takes the initiative to explore the combination of the...	Accept	The paper got split reviews: 1x reject, 1x borderline reject, 1x weak accept, 1x accept. All reviewers found the impressive performance on the challenging CARLA leaderboard to be a major strength of the paper. Reviewer concerns stem from two factors: a) not enough technical contribution to warrant publication at NeurI...	test	[ "VLQgyJR6lxx", "rRmrTi7eQp", "i5jmgA1FPZ", "2H8wWONoaf-", "pFz88kim1DH", "RMceg6fcoUj", "iBcyEmrT68A", "JdsCqKxsVJR", "F5cIuqKUX_X", "fRueL2xtGWn", "5soHQOeZmw", "sIIzUHVrgSC", "amjsb3Bjx9O", "vDuRZrui4R", "yAE_ePKKe6X", "2uoCsQDqU-v", "Dpg9GwhGgXy", "eS4cC7EOJh8", "rTkwPauIJq" ]	[ "author", "official_reviewer", "author", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the follow-up discussion.\n\n> Q3: Yes, I have seen the experiments on the fusion weight, but the unexplored part (and probably more critical, given the experiments with alpha values) is the \"situation\" detector. Seems like a very hard-coded rule in an otherwise learned approach.\n\nAgreed. Developin...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 4, 3, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 5, 5, 4 ]	[ "rRmrTi7eQp", "vDuRZrui4R", "2H8wWONoaf-", "yAE_ePKKe6X", "JdsCqKxsVJR", "iBcyEmrT68A", "fRueL2xtGWn", "5soHQOeZmw", "nips_2022_DhmYYrH_M3m", "eS4cC7EOJh8", "eS4cC7EOJh8", "Dpg9GwhGgXy", "Dpg9GwhGgXy", "2uoCsQDqU-v", "rTkwPauIJq", "nips_2022_DhmYYrH_M3m", "nips_2022_DhmYYrH_M3m", "...
nips_2022_jAL8Rt7HqB	Adaptive Attention Link-based Regularization for Vision Transformers	Although transformer networks are recently employed in the various vision tasks with the outperforming performance, large training data and a lengthy training time are required to train a model to disregard an inductive bias. Using trainable links between the channel-wise spatial attention of a pre-trained Convolutiona...	Reject	Four reviewers provided detailed feedback on this paper. The authors responded to the reviews and I appreciate the authors' comments and clarifications, specifically that each question/comment is addressed in detail. Additional experiments were also performed. The authors also uploaded a revised version of the paper. ...	test	[ "GK2am7ybwFK", "qlNe7hkPzf", "lt76YID-1Ps", "yBuKzhMW_VM", "cW8NYNyP02d", "Hq4ONy50sJs", "B_-4XuUVp8N", "UHK6pmc-Nr", "Jb_YkkGcN7e", "tlfAB9moQzf", "Xg7j2IIn4y", "4iP7wmbEuuK", "cCfTKzuVwO", "HDsJW7_bmq", "zZScJCw4V2y", "ClaTtsIXhAq", "i-O8m0K5Z9AL", "fQMhc4cObUA", "5yQVNosj4Rc",...	[ "author", "official_reviewer", "author", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official...	[ " The authors appreciate the reviewer for their detailed review of our manuscript and positive feedback. We are happy that our response has addressed your concerns.\n\nBest regards,\n\nAuthors", " Dear Authors,\n\nAfter having read the rebuttal in detail, my concerns have been addressed and I recommend the accept...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 6, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 4, 4 ]	[ "qlNe7hkPzf", "i-O8m0K5Z9AL", "cW8NYNyP02d", "pTJg_iFaJTM", "bhz8LzRV8q0", "Xg7j2IIn4y", "Xg7j2IIn4y", "4iP7wmbEuuK", "pTJg_iFaJTM", "bhz8LzRV8q0", "56HfaXRneGe", "Swgcg0vQvD0", "Swgcg0vQvD0", "Swgcg0vQvD0", "56HfaXRneGe", "56HfaXRneGe", "fQMhc4cObUA", "pTJg_iFaJTM", "bhz8LzRV8q0...
nips_2022_cj6K4IWVomU	Rotation-Equivariant Conditional Spherical Neural Fields for Learning a Natural Illumination Prior	Inverse rendering is an ill-posed problem. Previous work has sought to resolve this by focussing on priors for object or scene shape or appearance. In this work, we instead focus on a prior for natural illuminations. Current methods rely on spherical harmonic lighting or other generic representations and, at best, a si...	Accept	The paper introduces a rotation-equivariant conditional spherical neural fields for illumination priors. Reviewers mostly like the novelty of the proposed approach, its fit for the considered task of illumination priors, technical soundness and experimental evaluation that is thorough and shows merits of the approach. ...	train	[ "5Nh617Vxq6F", "BLyyRGmBm6X", "m91U7bas5X", "QPRoW-lEu4w", "QCN8QTSpJRD", "TJ2XkGmm22", "RkkH4MQVTUP", "ofI1LGV2GQc", "KK88f4KUEtB", "XwS44e70ky", "gijX96DtHC2", "0vnYhBVD64m" ]	[ "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for the response and the updated manuscript. The rebuttal clearly addresses my concerns, including ablation without equivariance (at different latent code dimensions as well), and implementation details about the choice of latent code dimensions and resolution of environment maps that can help reproduce...	[ -1, -1, -1, -1, -1, -1, -1, -1, 7, 3, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 5, 4, 2, 4 ]	[ "QPRoW-lEu4w", "m91U7bas5X", "TJ2XkGmm22", "0vnYhBVD64m", "gijX96DtHC2", "RkkH4MQVTUP", "XwS44e70ky", "KK88f4KUEtB", "nips_2022_cj6K4IWVomU", "nips_2022_cj6K4IWVomU", "nips_2022_cj6K4IWVomU", "nips_2022_cj6K4IWVomU" ]
nips_2022_8LE06pFhqsW	E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance	A critical challenge in multi-agent reinforcement learning(MARL) is for multiple agents to efficiently accomplish complex, long-horizon tasks. The agents often have difficulties in cooperating on common goals, dividing complex tasks, and planning through several stages to make progress. We propose to address these chal...	Accept	This paper deals with complex long-horizon tasks with multi-agent RL. The authors propose E-MAPP method that leverages parallel programs to guide multiple agents with goals to accomplish the task jointly. Generally, this paper is with an interesting idea and has sound technical contributions. The presentation is a bonu...	train	[ "ABHKPGESPQ", "RfikRszirVV", "N_hNxASIfKS", "aBEEmOx2aZy", "hPjFyilPyv2", "S1fHcsbsbg", "dlNHsV0sXK", "C_iJXUI9WuU", "JEtDjQWkHy2", "4d39UPGM5rZ", "JmjhIdXayWV", "hJBx41_JTt9", "MGMt1ghKVa" ]	[ "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for your extensive rebuttal and additional experimentations; I especially appreciate the results showing performance in the partially-observed setting. As several of my proposed weaknesses have been addressed I will increase my score to a 6. I struggle to go above this score for many of the same reasons...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 3 ]	[ "RfikRszirVV", "MGMt1ghKVa", "C_iJXUI9WuU", "MGMt1ghKVa", "MGMt1ghKVa", "hJBx41_JTt9", "hJBx41_JTt9", "hJBx41_JTt9", "JmjhIdXayWV", "nips_2022_8LE06pFhqsW", "nips_2022_8LE06pFhqsW", "nips_2022_8LE06pFhqsW", "nips_2022_8LE06pFhqsW" ]
nips_2022_htM1WJZVB2I	Vision GNN: An Image is Worth Graph of Nodes	Network architecture plays a key role in the deep learning-based computer vision system. The widely-used convolutional neural network and transformer treat the image as a grid or sequence structure, which is not flexible to capture irregular and complex objects. In this paper, we propose to represent the image as a gra...	Accept	This paper proposes to explore the graph structure of images by considering patches as nodes, where the graph is constructed by connecting nearest neighbors. Extensive experiments on various visual tasks, i.e., image recognition and object detection have demonstrated the effectiveness of the proposed ViG. All the revie...	train	[ "DhbzYk698Y", "fuc26t8aOb", "oeiiz8mSuXR", "0Y-VognFRHL", "T3VlqR7vIJX", "AVpHDIZwe61", "2zpOJaJjYLU", "i6uOZ2fKwUH", "_tIwhPuP2_o" ]	[ "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " After seeing other reviewers' comments and the received freedback from the authors, I keep my score as is. The paper is clear and has its clear novelty beyond vision transformer.", " Thanks for the valuable comments. We respond to weaknesses and questions in the following.\n\n> Q1:\nBased on my experience, ...	[ -1, -1, -1, -1, -1, 4, 7, 8, 8 ]	[ -1, -1, -1, -1, -1, 4, 5, 5, 4 ]	[ "fuc26t8aOb", "_tIwhPuP2_o", "i6uOZ2fKwUH", "AVpHDIZwe61", "2zpOJaJjYLU", "nips_2022_htM1WJZVB2I", "nips_2022_htM1WJZVB2I", "nips_2022_htM1WJZVB2I", "nips_2022_htM1WJZVB2I" ]
nips_2022_7a2IgJ7V4W	Semi-supervised Vision Transformers at Scale	We study semi-supervised learning (SSL) for vision transformers (ViT), an under-explored topic despite the wide adoption of the ViT architectures to different tasks. To tackle this problem, we use a SSL pipeline, consisting of first un/self-supervised pre-training, followed by supervised fine-tuning, and finally semi-s...	Accept	This paper explores Semi-ViT, a semi-supervised learning approach for vision transformers. Semi-VIT build-on three stages pipeline such as SimCLRv2. The authors introduce a probabilistic mixup for the semi-supervised finetuning stage which gives consistent experimental improvements. Semi-ViT shows strong empirical res...	test	[ "3pxHGebqe3V", "6gUqPKzFzMM", "8syA9Negenm", "xZo1QIywRB5", "porVH-KIsTa", "VN2h-VVB27ZA", "u7LZRmqPEg9", "qsCJJ1nS7X4", "vRNddoCQ22W", "sKpQmAYiYK1", "J8xafR-ISSs", "Vt1HdGSp6u1" ]	[ "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Dear reviewer, thanks for taking your time to read our responses. We have tried our best to answer your questions and address your concerns. Is there still any further confusion or concern we can help you to address? If it is still about the technical novelty, we appreciate if the reviewer could also read the oth...	[ -1, -1, -1, -1, -1, -1, -1, -1, 4, 8, 4, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 3, 5, 4, 4 ]	[ "8syA9Negenm", "xZo1QIywRB5", "qsCJJ1nS7X4", "u7LZRmqPEg9", "Vt1HdGSp6u1", "J8xafR-ISSs", "sKpQmAYiYK1", "vRNddoCQ22W", "nips_2022_7a2IgJ7V4W", "nips_2022_7a2IgJ7V4W", "nips_2022_7a2IgJ7V4W", "nips_2022_7a2IgJ7V4W" ]
nips_2022_gtCPWaY5bNh	Deep Model Reassembly	In this paper, we explore a novel knowledge-transfer task, termed as Deep Model Reassembly (DeRy), for general-purpose model reuse. Given a collection of heterogeneous models pre-trained from distinct sources and with diverse architectures, the goal of DeRy, as its name implies, is to first dissect each model into dis...	Accept	This paper proposes an interesting new way to think about how to use a model zoo of pre-trained models: extract modular building blocks that are swappable from the networks and then stitch them together. To do the former, a cover set optimization methods is proposed, and the blocks can then be combined in a way that ...	test	[ "bI9ScNdvKn", "E4_iG2sao3v", "mxPVFQ22pM", "VdiJ8ooV10j", "foaAVaWbzdG", "EYsFvLP2T6Y", "szRgeO3AtEF", "r1mhNcHzmJv", "3jWusBXyE_I", "kZjksFZKLP2", "vD--DKTNL-L", "1o4P2MmYS8a", "6Uw9xMIQA-g", "dwlyT1q7-9k", "XjfgzI9s2s8", "CwuGsPiWqjA" ]	[ "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " I thank the authors and appreciate their effort in improving the manuscript. To summarize, all of my concerns are now well addressed by the authors and hence I am increasing my initial score to Strong Accept.", " Thank you for the detailed response that resolves most of my concerns. As the first effort toward r...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 8, 8, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 4 ]	[ "mxPVFQ22pM", "szRgeO3AtEF", "VdiJ8ooV10j", "EYsFvLP2T6Y", "6Uw9xMIQA-g", "1o4P2MmYS8a", "kZjksFZKLP2", "CwuGsPiWqjA", "CwuGsPiWqjA", "CwuGsPiWqjA", "XjfgzI9s2s8", "XjfgzI9s2s8", "dwlyT1q7-9k", "nips_2022_gtCPWaY5bNh", "nips_2022_gtCPWaY5bNh", "nips_2022_gtCPWaY5bNh" ]
nips_2022_ebuR5LWzkk0	Are You Stealing My Model? Sample Correlation for Fingerprinting Deep Neural Networks	An off-the-shelf model as a commercial service could be stolen by model stealing attacks, posing great threats to the rights of the model owner. Model fingerprinting aims to verify whether a suspect model is stolen from the victim model, which gains more and more attention nowadays. Previous methods always leverage the...	Accept	The reviewers agreed that the proposed method and validation overall are a good contribution. We urge the authors to update their paper to reflect the discussed clarifications, e.g., regarding the threat models in use.	train	[ "SemNRKkXLA-", "MqcMfWeGMx2", "nZXw-maTc0E", "vdr-fHSs4S5", "o8qWSaS0Tym", "925tQrtiS2", "DZq7fLYPBn", "wnByfUKTWT4", "qPmjf9ft3EP", "QPq-D_G_fT", "_eCKDlIUmTn", "zrEL33sttL", "sXRdtMW-5-Y", "kGN31Bvybdd", "NqpsASREIvR" ]	[ "author", "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks again for your support, the detailed reviews, and the suggestions for improvement!", " Thank you very much for your efforts in addressing these concerns. I maintain my rating and lean to accept this paper.", " Dear reviewer, \n\nThanks again for your thoughtful review. Does our response address your qu...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 4 ]	[ "MqcMfWeGMx2", "_eCKDlIUmTn", "sXRdtMW-5-Y", "o8qWSaS0Tym", "925tQrtiS2", "NqpsASREIvR", "wnByfUKTWT4", "qPmjf9ft3EP", "NqpsASREIvR", "kGN31Bvybdd", "zrEL33sttL", "sXRdtMW-5-Y", "nips_2022_ebuR5LWzkk0", "nips_2022_ebuR5LWzkk0", "nips_2022_ebuR5LWzkk0" ]
nips_2022_xL8sFkkAkw	Towards Theoretically Inspired Neural Initialization Optimization	Automated machine learning has been widely explored to reduce human efforts in designing neural architectures and looking for proper hyperparameters. In the domain of neural initialization, however, similar automated techniques have rarely been studied. Most existing initialization methods are handcrafted and highly de...	Accept	The paper introduces a new procedure to initialize the optimisation in training process of DNN models, including the recent ViT architecture. All the reviewers recommend acceptance and appreciate the promising empirical results backed by the strong theoretical foundations. AC recommends acceptance as well.	test	[ "ZGxmr3h_hns", "6rfdopQ8um4", "Lk1BmkA5QMc", "mIrezaM4l_I", "KsM-p-pn3_t", "5sWj80CTSh", "9mHbJHbrK-y", "2gd-f-2IYgh", "AgKuBcv1BFf", "fMDsKy4Jfc", "Ns4bRDT3ySS", "PSlLuTudKeb", "Om0dU8txmM-", "hHD-oBKDM5_", "a8HrRb-465T", "Txm4DVqI58A", "I_Zls_qdBc6", "URG-X4GXfRX" ]	[ "author", "official_reviewer", "author", "author", "official_reviewer", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for appreciating our work. We are sorry that there are only a few hours left before the discussion deadline. We will be in a hurry for the revision version because we also need to consider how to fit in 9 pages after the revision and adding more results and discussions. But we would like to summarize the r...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 6, 6, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 3 ]	[ "6rfdopQ8um4", "AgKuBcv1BFf", "2gd-f-2IYgh", "KsM-p-pn3_t", "5sWj80CTSh", "9mHbJHbrK-y", "PSlLuTudKeb", "fMDsKy4Jfc", "a8HrRb-465T", "Ns4bRDT3ySS", "URG-X4GXfRX", "I_Zls_qdBc6", "hHD-oBKDM5_", "Txm4DVqI58A", "nips_2022_xL8sFkkAkw", "nips_2022_xL8sFkkAkw", "nips_2022_xL8sFkkAkw", "n...
nips_2022_QrK0WDLVHZt	Optimal Gradient Sliding and its Application to Optimal Distributed Optimization Under Similarity	We study structured convex optimization problems, with additive objective $r:=p + q$, where $r$ is ($\mu$-strongly) convex, $q$ is $L_q$-smooth and convex, and $p$ is $L_p$-smooth, possibly nonconvex. For such a class of problems, we proposed an inexact accelerated gradient sliding method that can skip the gradient ...	Accept	The paper extends gradient sliding to the situation where both functions are smooth and the sum is strongly convex. The resulting algorithm is then applied to distributed optimization settings and similarity assumptions, where it jointly achieves optimal gradient evaluations and communication complexities, improving on...	train	[ "jbp5JCocAB", "YAw2pncJ2k0", "PWS13jW8hrW", "doy3gPHkLK", "eOKzjRUkgzO", "IC_zi4a9IAK", "S6uwaEK-To", "mz4HIW79FZ6", "34z5ZUuKTpS", "LtobKKzTxEy", "5Fhzr9oYh87T", "-9eSCIFk4_z", "oE2AxN_wQD", "MqKLv3GFmCo", "XFPWSS9RP9", "e2eWwStdvc7", "Wl-m5TaTRup", "n_zdf4pi6t-", "3252QHkc7NS",...	[ "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "official_reviewer", "author", "official_reviewer", "official_reviewer", "author", "author", ...	[ " We greatly thank Reviewer 21CM for the response, important comments, and positive final feedback!", " Thanks for the detailed reply. I do not have any more questions. I would like to raise my score. ", " Thank you for the response!\n\nAt the moment we are discussing this with Reviewer disq.\nPlease, r...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 7, 6, 4 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 3, 2 ]	[ "YAw2pncJ2k0", "rh9efOzqPbr", "doy3gPHkLK", "y-8DB4NSnRl", "mz4HIW79FZ6", "34z5ZUuKTpS", "LtobKKzTxEy", "KrL9Kg2Glzd", "aqFyn9WBywqT", "qNHVaZv3kNi", "nips_2022_QrK0WDLVHZt", "MqKLv3GFmCo", "e2eWwStdvc7", "b_mc53LVoAk", "Wl-m5TaTRup", "3252QHkc7NS", "n_zdf4pi6t-", "F7iPpsR-9-", "...
nips_2022_Y4vT7m4e3d	Decentralized Local Stochastic Extra-Gradient for Variational Inequalities	We consider distributed stochastic variational inequalities (VIs) on unbounded domains with the problem data that is heterogeneous (non-IID) and distributed across many devices. We make a very general assumption on the computational network that, in particular, covers the settings of fully decentralized calculations wi...	Accept	The paper studies decentralized local stochastic extra-gradient for variational inequalities. An extra-gradient method is developed for this problem. Theoretical results are established and complemented by simulations. While there were some concerns about the novelty of the work in the initial review, the authors adequ...	val	[ "ge54pU1J13", "Qa17JRmBc4J", "qdRDmLAGMY", "uObtIVRaBoT", "XJ7DSdAmDfbT", "S8tFexfaKXyw", "7eZ1zkwJlg", "eqAhRRstvfL", "S5Z8vNsCscv", "TdI3wL1pUfe", "WOl2gleeOGh", "w2ckSbpKWc", "hQtcddfGG8", "zl6qj2PXtaT", "UMI4QsA_nSE" ]	[ "author", "author", "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We are very grateful to Reviewer dmBR for the response! We are especially grateful for the careful handling of our text! Using Reviewer's response, we tried to make our paper better.\n\n> **The current algorithm includes diffusion strategies on the clients. It has been known diffusion strategies work in distr...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 6, 3, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 5, 4, 3 ]	[ "uObtIVRaBoT", "qdRDmLAGMY", "TdI3wL1pUfe", "S5Z8vNsCscv", "nips_2022_Y4vT7m4e3d", "7eZ1zkwJlg", "eqAhRRstvfL", "UMI4QsA_nSE", "zl6qj2PXtaT", "hQtcddfGG8", "w2ckSbpKWc", "nips_2022_Y4vT7m4e3d", "nips_2022_Y4vT7m4e3d", "nips_2022_Y4vT7m4e3d", "nips_2022_Y4vT7m4e3d" ]
nips_2022_CZNFw38dDDS	P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting	Nowadays, pre-training big models on large-scale datasets has become a crucial topic in deep learning. The pre-trained models with high representation ability and transferability achieve a great success and dominate many downstream tasks in natural language processing and 2D vision. However, it is non-trivial to promot...	Accept	The paper presents a method of prompt tuning to transfer 2D pre-trained weights to tackling 3D understanding problems. All reviewers are positive about the novelty of the method. With large 2D pretrained models, higher performances are still expected from xwSJ, which is also a reasonable comment. Other 3D understanding...	train	[ "wfj_ioPAs5Gl", "sqxz9DtUOVt", "5otA25gZuV0", "wXY8HOp-0c4", "eO6Fqr4bZFp", "kqe3QaivO0Y", "6q_BZXt02KxE", "YZmrhk1BSG", "ubT1Uqey4z", "3IImbi3g0GB", "s2-jiHxiMt3", "w3Lv1dxR95Z", "GoAQDbVo5CE", "wggKVfpXQ5I", "GvGKoJFSsb0", "Nj0LjORO4JM", "YqQZsJe3YaT", "Gt9U0hrzKne", "Dyyhuw-Vb...	[ "author", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for upgrading your score and providing valuable feedback. We will update our revised paper according to our discussions. Thank you again for your insightful and constructive suggestions that improve paper quality!", " Thanks for your responses, which I believe are reasonable. Considering that these impor...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 6, 4, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 2, 4, 5, 3 ]	[ "sqxz9DtUOVt", "kqe3QaivO0Y", "YZmrhk1BSG", "ubT1Uqey4z", "GoAQDbVo5CE", "6q_BZXt02KxE", "s2-jiHxiMt3", "Dyyhuw-Vbo", "3IImbi3g0GB", "Gt9U0hrzKne", "w3Lv1dxR95Z", "YqQZsJe3YaT", "Nj0LjORO4JM", "GvGKoJFSsb0", "nips_2022_CZNFw38dDDS", "nips_2022_CZNFw38dDDS", "nips_2022_CZNFw38dDDS", ...
nips_2022_NQFFNdsOGD	Your Transformer May Not be as Powerful as You Expect	Relative Positional Encoding (RPE), which encodes the relative distance between any pair of tokens, is one of the most successful modifications to the original Transformer. As far as we know, theoretical understanding of the RPE-based Transformers is largely unexplored. In this work, we mathematically analyze the power...	Accept	This paper studies relative positive embeddings based Transformers. The authors present a negative result that there exist continuous sequence-to-sequence functions that relative based Transformers cannot approximate (irrespective of the depth and width of the network). The authors then propose a novel attention module...	train	[ "kmIhJGXk3B", "YIlkYrGKH4z", "VBORkb5LxR7", "1aY_Bc4QiP1", "KfWrSZHaD-", "gJ0GvGNF17dh", "GQcMMKhC0q3", "JI7fG4WY77L", "5yosMZcm_W", "mUZQkCHm4YI", "Dxl0lYEnx_z", "lCVBF1aW-_Y", "pdA4B0WIkU", "MDPWUjwa6DE", "UDqgijb7kqQ", "KXCso_8veZB" ]	[ "author", "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We sincerely thank you for your appreciation of our work! Your feedback is insightful to help us improve our paper. Thanks!", " Thanks for the authors' responses. Overall, I think this is a practical method with good theoretical proof. The paper writing, mathematical analysis, and experiments on kinds of modali...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 8, 8, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 3, 1 ]	[ "YIlkYrGKH4z", "gJ0GvGNF17dh", "KfWrSZHaD-", "nips_2022_NQFFNdsOGD", "mUZQkCHm4YI", "lCVBF1aW-_Y", "pdA4B0WIkU", "pdA4B0WIkU", "MDPWUjwa6DE", "UDqgijb7kqQ", "KXCso_8veZB", "nips_2022_NQFFNdsOGD", "nips_2022_NQFFNdsOGD", "nips_2022_NQFFNdsOGD", "nips_2022_NQFFNdsOGD", "nips_2022_NQFFNds...
nips_2022_2ktj0977QGO	Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization	Multi-instance learning (MIL) deals with objects represented as bags of instances and can predict instance labels from bag-level supervision. However, significant performance gaps exist between instance-level MIL algorithms and supervised learners since the instance labels are unavailable in MIL. Most existing MIL algo...	Accept	The paper studies multiple instance learning (MIL) by treating bags as auxiliary information, aiming to identify invariant causal representations using only bag labels available in the MIL setting. To achieve identifiability, it is assumed that the prior distribution over the instance latent variables belongs to the no...	val	[ "JuI44NupTW4", "jjanCzuIkU", "0CU0jl98tcR", "BeYw_NUCHdF", "Bci25bSSIe2", "XLyWgb7mYlX", "gHC_YfPibF", "FavpOhwP8xm", "d0DKQ9Bb7F8", "-9_g5jGXKNJ", "MeuO5FtuWtI", "jsvfpG9LnTq", "N5hQmfQi3AZ", "bvTLqovApN_", "v36CVg-7opp", "md4bbzox3t8", "yTq-NdOq5CM", "ZpFNe_I7OY" ]	[ "author", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you very much for reading our responses and raising the score! \n\nWe will certainly incorporate the discussions into the manuscript. And also, thanks very much for the dataset recommendations; we will run experiments with the suggested datasets in the future.\n\n**Q: Did you tune the hyperparameters for th...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 7, 8, 4 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 3, 5, 4 ]	[ "jjanCzuIkU", "-9_g5jGXKNJ", "XLyWgb7mYlX", "Bci25bSSIe2", "jsvfpG9LnTq", "bvTLqovApN_", "FavpOhwP8xm", "N5hQmfQi3AZ", "nips_2022_2ktj0977QGO", "v36CVg-7opp", "v36CVg-7opp", "ZpFNe_I7OY", "md4bbzox3t8", "yTq-NdOq5CM", "nips_2022_2ktj0977QGO", "nips_2022_2ktj0977QGO", "nips_2022_2ktj0...
nips_2022_Siv3nHYHheI	Online Training Through Time for Spiking Neural Networks	Spiking neural networks (SNNs) are promising brain-inspired energy-efficient models. Recent progress in training methods has enabled successful deep SNNs on large-scale tasks with low latency. Particularly, backpropagation through time (BPTT) with surrogate gradients (SG) is popularly used to enable models to achieve h...	Accept	The authors propose an online training algorithm (OTTT) for spiking neural networks (SNNs) using eligibility traces and instantaneous loss values. They show empirically that this method performs better than previous ones in feed-forward spiking neural networks. All reviewers agree that the empirical results are impres...	test	[ "oLKVV80Nozw", "thmBtJmnP2n", "x1cpu2CSdHK", "wA3T4kFjAuV", "VitYfTW-Vxe", "-w21uEDkDN7", "B_LH-4NCNx", "DgINWVYhXZ", "rT7sttFiw-", "tv0b3LzKyUq", "U3BosS7lzm2", "2DoPlOk4XNe", "SzWqUlzjrF", "xLDk7a-OJDu", "PQNAUilIClb", "EvOlY615l4W", "WgB_bPmVz-a", "JejHTho56Vh", "evzCJ1zUn5W" ...	[ "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for the valuable suggestion and we will clarify this in the following revision. Yes, for each input sample, the network is reset at time step 0, and at each discrete time step $t$ the input at time step $t$ is passed to the network, with total $T$ time steps. For static images, the input at all time ste...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 7, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 3 ]	[ "x1cpu2CSdHK", "wA3T4kFjAuV", "xLDk7a-OJDu", "SzWqUlzjrF", "-w21uEDkDN7", "evzCJ1zUn5W", "nips_2022_Siv3nHYHheI", "evzCJ1zUn5W", "evzCJ1zUn5W", "evzCJ1zUn5W", "evzCJ1zUn5W", "JejHTho56Vh", "JejHTho56Vh", "JejHTho56Vh", "WgB_bPmVz-a", "WgB_bPmVz-a", "nips_2022_Siv3nHYHheI", "nips_20...
nips_2022_y5ziOXtKybL	Asymptotic Properties for Bayesian Neural Network in Besov Space	Neural networks have shown great predictive power when dealing with various unstructured data such as images and natural languages. The Bayesian neural network captures the uncertainty of prediction by putting a prior distribution for the parameter of the model and computing the posterior distribution. In this paper, w...	Accept	This work conducts novelty study and extends the results on asymptotic convergence of Bayesian ReLU networks from the Hölder space to the more general Besov space. The reviewers consider it "a strong theoretical results closing a gap for posterior contraction of BNN in Besov spaces". The authors' feedback addressed a...	train	[ "MU0W4dh2stK", "X1xWcqGvks", "v43t0jJ07vJ", "gusvobF1w4a", "C9EXjBLuqSj", "AIMZ-WrVGHS", "i3wTSVlBbWN", "75nQhJ6gQL8", "S8Ougl3jOfM", "hdXKYNRtVYh", "UU1Amylx77", "Y5z3ztdZWOM" ]	[ "official_reviewer", "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you very much for this clarification. It is clear now. ", " Thanks for your constructive questions.\n\n## Q. \n\n> The question about the learnable hyperparameters is about the prior derived in the paper, which seems to be a fixed prior. However, we normally set a learnable prior to practice. Will this le...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 7, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 2 ]	[ "gusvobF1w4a", "v43t0jJ07vJ", "i3wTSVlBbWN", "C9EXjBLuqSj", "S8Ougl3jOfM", "nips_2022_y5ziOXtKybL", "hdXKYNRtVYh", "UU1Amylx77", "Y5z3ztdZWOM", "nips_2022_y5ziOXtKybL", "nips_2022_y5ziOXtKybL", "nips_2022_y5ziOXtKybL" ]
nips_2022_iKKfdIm81Jt	Planning for Sample Efficient Imitation Learning	Imitation learning is a class of promising policy learning algorithms that is free from many practical issues with reinforcement learning, such as the reward design issue and the exploration hardness. However, the current imitation algorithm struggles to achieve both high performance and high in-environment sample effi...	Accept	This paper introduces a simple approach that improves the sample efficiency of model-based RL for continuous control tasks. The proposed approach, EfficientImitate builds on EfficientZero and uses a hybrid BC-AIL training scheme. The contribution is relatively simple and is shown through satisfactory experiments to g...	train	[ "0svlHjnEb3b", "BL9UN01uWR", "5jQIJlNAe_k", "VZbL-4wEEf", "0NQ-VCh5Bex", "kOqy2Fzo9Ds", "Mj13WOQOia", "VbPH5LO8aVC" ]	[ "official_reviewer", "official_reviewer", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for the response.\n\nYour explanations make sense. I would encourage you to propagate them to the paper in order to help the readers also to build up the intuitions that you have.\n\nThank you for conducting additional experiments.", " Thanks for the response. The additional discussions and visualizat...	[ -1, -1, -1, -1, -1, 7, 5, 7 ]	[ -1, -1, -1, -1, -1, 3, 3, 4 ]	[ "0NQ-VCh5Bex", "5jQIJlNAe_k", "VbPH5LO8aVC", "Mj13WOQOia", "kOqy2Fzo9Ds", "nips_2022_iKKfdIm81Jt", "nips_2022_iKKfdIm81Jt", "nips_2022_iKKfdIm81Jt" ]
nips_2022_nE8IJLT7nW-	Peripheral Vision Transformer	Human vision possesses a special type of visual processing systems called peripheral vision. Partitioning the entire visual field into multiple contour regions based on the distance to the center of our gaze, the peripheral vision provides us the ability to perceive various visual features at different regions. In this...	Accept	The paper proposes a transformer architecture that models human-like peripheral vision. Experiment results show it achieves good performance. All the reviewers consider the paper above the bar. They like the novelty and the strong empirical performance. The AC finds no reason to object.	train	[ "gRhmhLejDe", "VAzHPQyi5kA", "FCn4erTKtVh", "qmWH2AiC4jA", "uhQLGTn-nMA", "8-2Gr-7BCBJ", "tirRpvy69aM", "zjit52bYJpz", "HNLttS6A7GO", "P6VF4FyZ0fv", "LPSF9yFx0To", "oUWfi5FLbL0", "MvNbBKrlnw0u", "NVwVNq3niaB", "tFa302Plyji", "fVUXM17N8A6", "lRp_nQ9Ggtc", "5dV3nUbi2-G", "GEALQhg2A...	[ "author", "official_reviewer", "author", "author", "author", "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We truly appreciate the positive evaluations and will do our best to reflect the comments as much as possible.", " Thank you authors for your message and flagging the missing score change. I just upgraded my score to reflect the changes.\n\nBest wishes.", " We again thank the reviewer for the professional, in...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 7, 7, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 4, 3 ]	[ "VAzHPQyi5kA", "qmWH2AiC4jA", "HNLttS6A7GO", "8-2Gr-7BCBJ", "nips_2022_nE8IJLT7nW-", "MvNbBKrlnw0u", "P6VF4FyZ0fv", "MvNbBKrlnw0u", "LPSF9yFx0To", "fVUXM17N8A6", "NVwVNq3niaB", "nips_2022_nE8IJLT7nW-", "B13llK6vyqX", "5dV3nUbi2-G", "lRp_nQ9Ggtc", "GEALQhg2Ay", "nips_2022_nE8IJLT7nW-"...
nips_2022_QzFJmwwBMd	ZARTS: On Zero-order Optimization for Neural Architecture Search	Differentiable architecture search (DARTS) has been a popular one-shot paradigm for NAS due to its high efficiency. It introduces trainable architecture parameters to represent the importance of candidate operations and proposes first/second-order approximation to estimate their gradients, making it possible to solve N...	Accept	This paper aims to solve the instability issues of differentiable architecture search (DARTS) using zero-order optimization. Three different optimization techniques are proposed and their efficacy is demonstrated successfully on several benchmark datasets and different variants of DARTS. Although there are some concern...	train	[ "FCfSK2BccN9", "Z3ijPUw5-y3b", "lJ2fbTsOUL", "JHcxZ1CrWCW", "_0kY_GlMofa", "OoCAViMMr9d", "CSQ8Vju7qbE", "J0RqUeAMpG" ]	[ "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for your detailed response, most of my concerns are addressed. I have raised my rating to borderline accept.", " Thank you for your thorough and valuable comments. We answer your questions as follows in the hope of resolving your concerns.\n\n**Q1: ZARTS is more time-consuming than other DARTS-based meth...	[ -1, -1, -1, -1, -1, 5, 7, 8 ]	[ -1, -1, -1, -1, -1, 3, 4, 5 ]	[ "JHcxZ1CrWCW", "J0RqUeAMpG", "CSQ8Vju7qbE", "_0kY_GlMofa", "OoCAViMMr9d", "nips_2022_QzFJmwwBMd", "nips_2022_QzFJmwwBMd", "nips_2022_QzFJmwwBMd" ]
nips_2022_IvnoGKQuXi	Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization	In label-noise learning, estimating the transition matrix plays an important role in building statistically consistent classifier. Current state-of-the-art consistent estimator for the transition matrix has been developed under the newly proposed sufficiently scattered assumption, through incorporating the minimum volu...	Accept	This work addresses the problem of estimating the transition matrix by using forward-backward cycle-consistency, with class-dependent noisy labels. There is merit in this work, as the proposed method might encourage the estimated transition matrix to converge to its optimal solution, without explicitly estimating the n...	train	[ "q-jl8H2tSdq", "5PfNLmDU34", "EHO_NmhT1sw", "uQWd1q8gVR", "KlZL5zUjWWb", "GuAwOXlqVcu", "xUf9OzGCPZ1", "OPQyVvltZ9T", "V6U8iKy2Bj2", "TvMG3-bAo1", "MIOejKv3wp", "cjdR3bgSbpN", "2fxE9Lc2-JJ", "_Qyy2D1kmnW", "fu_ImERHzeN", "mBOiYivWveG", "c4jY7sh1pan", "yrYAgR20Wj5", "PuN27q2z9E" ]	[ "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " The response well addresses my concern and I would keep my score.", " Dear reviewer 3zVp,\n\nIt seems we have addressed all your major concerns. Can you kindly reconsider the recommendation? Thanks very much.\n\nBest", " Thank you very much for your quick responses. Your comments have greatly helped improve t...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 8, 7, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 5, 5 ]	[ "cjdR3bgSbpN", "EHO_NmhT1sw", "KlZL5zUjWWb", "2fxE9Lc2-JJ", "GuAwOXlqVcu", "xUf9OzGCPZ1", "fu_ImERHzeN", "mBOiYivWveG", "nips_2022_IvnoGKQuXi", "mBOiYivWveG", "mBOiYivWveG", "yrYAgR20Wj5", "PuN27q2z9E", "c4jY7sh1pan", "mBOiYivWveG", "nips_2022_IvnoGKQuXi", "nips_2022_IvnoGKQuXi", "...
nips_2022_V3kqJWsKRu4	InsPro: Propagating Instance Query and Proposal for Online Video Instance Segmentation	Video instance segmentation (VIS) aims at segmenting and tracking objects in videos. Prior methods typically generate frame-level or clip-level object instances first and then associate them by either additional tracking heads or complex instance matching algorithms. This explicit instance association approach increase...	Accept	The paper discusses a method for online video instance segmentation. Reviewers appreciated the proposed method but raised concerns regarding difference of reported results to other papers, method being similar to prior work, and limited novelty. The rebuttal addressed most of the concerns prompting reviewers to increas...	val	[ "xaXCO9ap49N", "ZoyjWbtIIJB", "1sghoR7OYE", "Dn6jfb4sIeW", "_RYCw6tA4DD", "GrzJW7Opha", "4iLy3clB0Q3", "6HqW7pJpR-", "6HxE3UIM0gn", "w4T1rKUlF3n", "YIPUF-AjFZ", "fN1LZg_q6gK", "KKJPQeY5aE", "en4ag8a2oYD", "_dfeZn1T65", "e-w-M5WT3Hf", "B1zWW1R5IvR", "3L6ZJA3vGKb", "NFJ7wLIF63t", ...	[ "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_...	[ " Wow! It is very glad to hear that we address most of your concerns. Thank you very much for this kind rating upgrade. We are really delighted to hear this good news. Have a nice one!", " Thanks for your response and I'm feeling sorry for the delayed reply. The revised version of InsPro covers most of my concern...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 6, 5, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 5, 5 ]	[ "ZoyjWbtIIJB", "4iLy3clB0Q3", "Dn6jfb4sIeW", "6HqW7pJpR-", "KKJPQeY5aE", "6HxE3UIM0gn", "_dfeZn1T65", "3L6ZJA3vGKb", "YIPUF-AjFZ", "nips_2022_V3kqJWsKRu4", "fN1LZg_q6gK", "en4ag8a2oYD", "iBpk8uQqq8E", "bkTkc0HIqOk", "i3g4aiT5etZ", "B1zWW1R5IvR", "nips_2022_V3kqJWsKRu4", "NFJ7wLIF63...
nips_2022_aGFQDrNb-KO	Multi-dataset Training of Transformers for Robust Action Recognition	We study the task of robust feature representations, aiming to generalize well on multiple datasets for action recognition. We build our method on Transformers for its efficacy. Although we have witnessed great progress for video action recognition in the past decade, it remains challenging yet valuable how to train a ...	Accept	The paper proposes a co-training method for video representation learning, by training video transformers on multiple video datasets. The paper proposes two novel loss terms: informative loss and projection loss. The informative loss encourages the variance of each dimension in the embedding to be large. The projection...	train	[ "u8znSkxkW3M", "K5XPJiaOGGQ", "iOuevRk4Ecq", "GfuPRDEfzCr", "xSBxokVttq6", "fBFi2XNKUa_", "jOkuFm850-z", "OFMh8_NpsF_", "a7SyyN7UZKN" ]	[ "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Dear authors,\n\n Thank you for the clarification. My concerns have been addressed and I don't have further questions.", " Dear Reviewer iVPd, \nThank you very much again for the time and effort put into reviewing our paper. We believe that we have addressed all your concerns in our response. We have also follo...	[ -1, -1, -1, -1, -1, -1, 5, 5, 5 ]	[ -1, -1, -1, -1, -1, -1, 4, 4, 4 ]	[ "K5XPJiaOGGQ", "iOuevRk4Ecq", "xSBxokVttq6", "a7SyyN7UZKN", "OFMh8_NpsF_", "jOkuFm850-z", "nips_2022_aGFQDrNb-KO", "nips_2022_aGFQDrNb-KO", "nips_2022_aGFQDrNb-KO" ]
nips_2022_a8qX5RG36jd	LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model	Universally modeling all typical information extraction tasks (UIE) with one generative language model (GLM) has revealed great potential by the latest study, where various IE predictions are unified into a linearized hierarchical expression under a GLM. Syntactic structure information, a type of effective feature whic...	Accept	This paper proposes a latent adaptive structure-aware generative language model (GLM) to leverage syntactic knowledge for information extraction tasks. The proposed model incorporates a latent structure induction module that automatically induces tree-like structures akin to dependency and constituency trees. Experimen...	val	[ "uVMGhKHU04q", "eaTT5AoHY81", "HkMUAIRIkgH", "ogNoDsgUuvN", "K96IrfIsejW", "7ZnHCqstb3y", "l7TdtIvr2uU", "8rrYTAX4nV4", "BX_yt1PFy60", "mCjvPcStWp3" ]	[ "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you again for your acknowledgment. We representatively present the parsing results of the constituency syntax. Following are the experimental results of the grammar induction w.r.t. each tag, as you indicated. The results are the recall rates of the labels that were identified by the model (label recall). \...	[ -1, -1, -1, -1, -1, -1, -1, 7, 6, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, 3, 4, 3 ]	[ "HkMUAIRIkgH", "K96IrfIsejW", "7ZnHCqstb3y", "mCjvPcStWp3", "BX_yt1PFy60", "8rrYTAX4nV4", "nips_2022_a8qX5RG36jd", "nips_2022_a8qX5RG36jd", "nips_2022_a8qX5RG36jd", "nips_2022_a8qX5RG36jd" ]
nips_2022_Ojakr9ofova	Scalable Infomin Learning	The task of infomin learning aims to learn a representation with high utility while being uninformative about a specified target, with the latter achieved by minimising the mutual information between the representation and the target. It has broad applications, ranging from training fair prediction models against prote...	Accept	Summary: This paper develops an infomin-based representation method that based on the recently-proposed sliced mutual informaiton estimator. Unlike other methods, the proposed approach does not rely on an adversarial objective and provides tractable proxy-metric that eliminates the need for neural estimators of the...	train	[ "cn_PKrwR5xw", "hvoVdfYiwbY", "GFWg_R7mW0Z", "2bwJkktn7nN", "dPFdeme7-AF", "Isg1gxFA7H8", "l4HbSze2QC-", "2ibZBv8ZAGc", "KBp8iWkiAAJ", "0yCXVwNjE9Y", "3dWgIzjhqtE", "MzPMjm83zUp" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the authors' response. \n\nI am glad to see that the presentation of the paper significantly improves, and the authors add a pseudo algo comparison with adversarial learning based approaches as well as the CLUB baseline. I am mostly satisfied with the answers. Thus I update the score from 5 to 6.\n", ...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 7, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 3 ]	[ "dPFdeme7-AF", "GFWg_R7mW0Z", "2ibZBv8ZAGc", "l4HbSze2QC-", "KBp8iWkiAAJ", "nips_2022_Ojakr9ofova", "3dWgIzjhqtE", "MzPMjm83zUp", "0yCXVwNjE9Y", "nips_2022_Ojakr9ofova", "nips_2022_Ojakr9ofova", "nips_2022_Ojakr9ofova" ]
nips_2022_OzbkiUo24g	Linear tree shap	Decision trees are well-known due to their ease of interpretability. To improve accuracy, we need to grow deep trees or ensembles of trees. These are hard to interpret, offsetting their original benefits. Shapley values have recently become a popular way to explain the predictions of tree-based machine learning models...	Accept	Shapley values are a common tool used for evaluating feature importance. In this work the authors present a way to accelerate the computation of these values when the model used is a tree or an ensemble of trees. The algorithm presented has linear computational complexity with respect to the maximal depth of the tree $...	train	[ "HY6bStVUcF", "kRR8JpTRaQ", "CoFjWgrjo7S3", "FiQ3H_HFDBY", "2QhrYA20dRP", "yG61pcTtXhu", "AyIf5rs6eK", "oO3zrH5x17", "hbVQ7FQcVaH", "QHW_bhgkEQ9" ]	[ "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks to the authors for their response. A couple additional thoughts:\n\nAbout equation 11. I get that the two steps are replacing $M$ with $F(R)$ and partitioning subsets based on their size. The part that would be nice to reproduce is how you derive the new weights for each $S \\subseteq F(R) \\setminus i...	[ -1, -1, -1, -1, -1, 7, 7, 7, 7, 7 ]	[ -1, -1, -1, -1, -1, 4, 3, 3, 4, 3 ]	[ "FiQ3H_HFDBY", "AyIf5rs6eK", "yG61pcTtXhu", "hbVQ7FQcVaH", "oO3zrH5x17", "nips_2022_OzbkiUo24g", "nips_2022_OzbkiUo24g", "nips_2022_OzbkiUo24g", "nips_2022_OzbkiUo24g", "nips_2022_OzbkiUo24g" ]
nips_2022_L7P3IvsoUXY	CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks	Previous works have validated that text generation APIs can be stolen through imitation attacks, causing IP violations. In order to protect the IP of text generation APIs, recent work has introduced a watermarking algorithm and utilized the null-hypothesis test as a post-hoc ownership verification on the imitation mode...	Accept	The authors propose a watermarking technique (CATER) to claim ownership of text generation APIs in the presence of imitation attacks. Their main idea is based on the observation that in the state of the art by analyzing the word frequency in API responses as well as publicly available data, an adversary's odds to learn...	train	[ "2oFl72mOWjr", "szkVDD0Xa7E", "v7V0fWYCio8", "F4CqGaYKtE", "F_3t2JOyHUN", "WFsXxdRMQ8X", "HRantg3xX_J", "NIOM37eSuRr", "4s38ngKXvD9", "1aiX3vg3uqK", "Nz4g6yupWxg", "oCljCNcEf_a", "Z8_LU853CFs", "vP-tUydhfu", "9qTbOLGogi8", "2gy2pY_7QCr" ]	[ "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We would like to appreciate the reviewer’s encouraging comments and positive feedback, which has helped us polish our submission.", " We would like to appreciate the reviewer’s invaluable feedback, which has helped us improve our submission.", " Review EoSA here. Thanks a lot for clarifying my questions and c...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 8, 8, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 5, 5, 3 ]	[ "F4CqGaYKtE", "v7V0fWYCio8", "Z8_LU853CFs", "1aiX3vg3uqK", "oCljCNcEf_a", "NIOM37eSuRr", "Nz4g6yupWxg", "2gy2pY_7QCr", "9qTbOLGogi8", "vP-tUydhfu", "oCljCNcEf_a", "Z8_LU853CFs", "nips_2022_L7P3IvsoUXY", "nips_2022_L7P3IvsoUXY", "nips_2022_L7P3IvsoUXY", "nips_2022_L7P3IvsoUXY" ]
nips_2022_r__gfIasEdN	GAPX: Generalized Autoregressive Paraphrase-Identification X	Paraphrase Identification is a fundamental task in Natural Language Processing. While much progress has been made in the field, the performance of many state-of- the-art models often suffer from distribution shift during inference time. We verify that a major source of this performance drop comes from biases introduced...	Accept	This paper tackles a discriminative problem by a generative model, where the generation probabilities can be twisted to adjust negative samples’ weights. Reviewers generally found the paper interesting. However, one concern is that the paper only considers the paraphrase-identification problem, which sounds narrow. I...	train	[ "7iMFE7dX_0", "2a4GzyL9RnW", "965R0S5YURH", "xIRccp5hEBE", "2EUGPtA2G8v", "3_Mtp1MB9SY", "eMulUvWjlDR", "PxIQ7_LwsQA", "RfvPNef3xoo", "Yr4fWThj8z", "cp_PStZDSoz", "I4fa0I0t62F", "mP82RPxlAYw" ]	[ "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the authors' response.\n\nThe clarification about OODP and GAPX is helpful for the readers to navigate the results. I now realize that you've talked about this during Section 4.5, but again within that paragraph you are jumping back and forth between several different points and it's a bit hard to foll...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 7, 6, 8 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 4 ]	[ "PxIQ7_LwsQA", "xIRccp5hEBE", "2EUGPtA2G8v", "3_Mtp1MB9SY", "RfvPNef3xoo", "I4fa0I0t62F", "mP82RPxlAYw", "cp_PStZDSoz", "Yr4fWThj8z", "nips_2022_r__gfIasEdN", "nips_2022_r__gfIasEdN", "nips_2022_r__gfIasEdN", "nips_2022_r__gfIasEdN" ]
nips_2022_-me36V0os8P	Explaining Preferences with Shapley Values	While preference modelling is becoming one of the pillars of machine learning, the problem of preference explanation remains challenging and underexplored. In this paper, we propose \textsc{Pref-SHAP}, a Shapley value-based model explanation framework for pairwise comparison data. We derive the appropriate value functi...	Accept	Overall, the opinion about this paper is quite positive, especially because of its novelty: It establishes the first connection between preference learning and explainability/Shapley. In terms of presentation and technical soundness, the paper seems to be convincing, too. A few critical points (e.g., regarding the eval...	train	[ "hDEw369FlfG", "yk8XHcrp5nx", "SkVXgd4tMY", "dreOIp1tAEy", "g0VpxAlJgZN", "OaHeVajcbOEC", "4oMIseHy4J", "AQXcfpcezLDt", "aPztgJE0FxC", "OQra7A20cQV", "FoTx82LVwh-", "nz6jH_PYjU", "aj96iePqNlt", "459MSw9TPpS" ]	[ "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for your question!\n\nThe specific comparison done in appendix B is precisely meant to illustrate the importance of redefining the value function in order to make it suited for preferential data, i.e. to remove the features in conjunction with each other as the reviewer suggests -- and to assign Shapley...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 8, 5, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 3, 4, 4 ]	[ "yk8XHcrp5nx", "OaHeVajcbOEC", "dreOIp1tAEy", "aPztgJE0FxC", "4oMIseHy4J", "459MSw9TPpS", "aj96iePqNlt", "nz6jH_PYjU", "FoTx82LVwh-", "nips_2022_-me36V0os8P", "nips_2022_-me36V0os8P", "nips_2022_-me36V0os8P", "nips_2022_-me36V0os8P", "nips_2022_-me36V0os8P" ]
nips_2022_BgMz5LHc07R	C-Mixup: Improving Generalization in Regression	Improving the generalization of deep networks is an important open challenge, particularly in domains without plentiful data. The mixup algorithm improves generalization by linearly interpolating a pair of examples and their corresponding labels. These interpolated examples augment the original training set. Mixup has ...	Accept	This is an interesting and technically solid paper. The reviews are very consistent as well.	train	[ "ouRjGvMuAW", "SNqVKhQsEzC", "50SxbIVYjWO", "9YZGZLb9R9S", "W0ftybwZaWHR", "yB5PQCEWNZ9", "QKossfDUXj", "BxrqyNi1Sg6", "-HOglvVeGWV", "flhqX516Dcv", "5fMQvwqh8oB", "nuoFcIFFhfa", "ydhRzfzH47U", "FdhMe_kM15Q", "b7QcuAwTILhJ", "mz-7NozIMjF", "FU2cMGbgxjg", "BZfmljPbEvc", "aCGl7ONPf...	[ "author", "official_reviewer", "author", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_...	[ " Hi Reviewer 13Sq,\n\nThanks for pointing out this issue. We are sorry about the confusion. We indeed compared with AutoMix [2] (ECCV'2022) in our additional experiments. We made a mistake when adding the citation and have fixed this issue in the updated version. Many thanks!", " Thanks for your quick response. ...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 4 ]	[ "SNqVKhQsEzC", "50SxbIVYjWO", "9YZGZLb9R9S", "W0ftybwZaWHR", "QKossfDUXj", "BxrqyNi1Sg6", "FU2cMGbgxjg", "FdhMe_kM15Q", "FU2cMGbgxjg", "FdhMe_kM15Q", "nuoFcIFFhfa", "BZfmljPbEvc", "nips_2022_BgMz5LHc07R", "b7QcuAwTILhJ", "mz-7NozIMjF", "TX27y5JcMb2", "fszTYQufrlX", "aCGl7ONPfG", ...
nips_2022_dUYLikScE-	Infinite-Fidelity Coregionalization for Physical Simulation	Multi-fidelity modeling and learning is important in physical simulation related applications. It can leverage both low-fidelity and high-fidelity examples for training so as to reduce the cost of data generation yet still achieving good performance. While existing approaches only model finite, discrete fidelities, in ...	Accept	The paper tackles the multi-fidelity simulation problem by modeling the grid variation with NODE, coupled with a GP. Experiments on multiple physical simulators show better performance compared to baselines. Please also report computational efficiency and sample complexity in the final version.	train	[ "Sv3hSba0yMM", "_pAdCb7qtfhE", "h7tigo9ElCrf", "vguisfp_yB", "gpmjtArrWw", "857-h_swPh", "3oLfFVWj9ja", "xhi45D5WSH", "C4vXmUGM1Ex", "Ow8frKfLkyK" ]	[ "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for answering my questions. I've raised my score based on the response.\nGood luck", " C6: Does the proposed model support varying input and output dimensions at different fidelity levels?\n\nR6: Great question. Since the input to our model is the identify information of the problem, such as PDE paramete...	[ -1, -1, -1, -1, -1, -1, -1, 6, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, 4, 4, 4 ]	[ "_pAdCb7qtfhE", "h7tigo9ElCrf", "Ow8frKfLkyK", "gpmjtArrWw", "857-h_swPh", "C4vXmUGM1Ex", "xhi45D5WSH", "nips_2022_dUYLikScE-", "nips_2022_dUYLikScE-", "nips_2022_dUYLikScE-" ]
nips_2022_fzvDZ0mraPP	Giga-scale Kernel Matrix-Vector Multiplication on GPU	Kernel matrix-vector multiplication (KMVM) is a foundational operation in machine learning and scientific computing. However, as KMVM tends to scale quadratically in both memory and time, applications are often limited by these computational constraints. In this paper, we propose a novel approximation procedure coined ...	Accept	The authors propose an new approximation procedure for Kernel matrix-vector multiplication target to tall and skinny kernel matrices. The proposed method achieves significant speedups over the state-of-the-art GPU-based linear solver FALKON while sacrificing only small drops in accuracy due to approximation. The paper...	train	[ "K-nQyc8hMc", "q9Z3krHetpP", "epvIapVG1MTB", "zLJGuTysyP", "5aJa4Gbs9FpY", "2fmBTU988lV", "ztBDNqKmeE3", "5gIBTWBF9Ks", "cdPF9frpE5P", "KEWdZIQ51f" ]	[ "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " I'm grateful to the authors for their response to my questions. I will keep my score as accept.", " Thank you for your time and effort in reviewing the paper! We respond to your comments and questions below:\n\nQ1: I would like to to see some ablation studies and experiments on F^{2.5}M. \nA1: We have pro...	[ -1, -1, -1, -1, -1, -1, 7, 6, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, 4, 3, 2, 2 ]	[ "5aJa4Gbs9FpY", "KEWdZIQ51f", "cdPF9frpE5P", "5gIBTWBF9Ks", "ztBDNqKmeE3", "nips_2022_fzvDZ0mraPP", "nips_2022_fzvDZ0mraPP", "nips_2022_fzvDZ0mraPP", "nips_2022_fzvDZ0mraPP", "nips_2022_fzvDZ0mraPP" ]
nips_2022_nJt27NQffr	Self-Supervised Learning via Maximum Entropy Coding	A mainstream type of current self-supervised learning methods pursues a general-purpose representation that can be well transferred to downstream tasks, typically by optimizing on a given pretext task such as instance discrimination. In this work, we argue that existing pretext tasks inevitably introduce biases into th...	Accept	The paper in general received three positive feedbacks and ratings. The three reviewers all recognize the theoretical soundness of the paper, and the paper is also clearly presented with informative and strong experimental results. There is a few places making one reviewer less comfortable in terms of the exact effecti...	train	[ "1D5QseuDfao", "jhNmg6p4W44", "_CRwj_41D_3", "LOZdyTPyjUyY", "7Rshwe65owV", "JseAaEPPCRG", "kBn4idsJKm", "HNkE8jJcGhP", "TodRS3dY18", "W95okT9-Gr", "b6QZR_vTPX", "WYBS_UVgqaJ" ]	[ "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We sincerely thank the reviewer for providing the additional feedback. We address your concerns below.\n\n>\"Actually, in response point 1, Barlow Twins are supposed to reach 73.5\\%. So here, the extra two orders approximately indeed only provide a 0.1\\% improvement.\"\n\n**First, it should be clarified tha...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 5, 8 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 4, 4 ]	[ "_CRwj_41D_3", "LOZdyTPyjUyY", "7Rshwe65owV", "W95okT9-Gr", "JseAaEPPCRG", "b6QZR_vTPX", "WYBS_UVgqaJ", "TodRS3dY18", "W95okT9-Gr", "nips_2022_nJt27NQffr", "nips_2022_nJt27NQffr", "nips_2022_nJt27NQffr" ]
nips_2022_KglFYlTiASW	Neural Transmitted Radiance Fields	Neural radiance fields (NeRF) have brought tremendous progress to novel view synthesis. Though NeRF enables the rendering of subtle details in a scene by learning from a dense set of images, it also reconstructs the undesired reflections when we capture images through glass. As a commonly observed interference, the ref...	Accept	This paper proposes a novel neural radiance field rendering method that is dealing with specular reflection on the object’s surface. The authors present a novel method to solve the limitation of the existing NeRF-based methods for the scenes behind the transparent surfaces with specular reflection. The review results a...	train	[ "cK17dISDzl7", "1-uMB9cROD", "yxqwaJ88gtE", "MJS4EiHsPeo", "GeVmhlOwaz", "EPlijxvg5fo", "oz2LoycuaC_", "hnW7O_Pk0y", "vzSCNbbiLkB", "3hM9QqO5dLS", "Grf62Qo59r0", "KPpd4YA8U_", "wmvYGXr6tLb", "AicpL3uDBb", "6k3_tBmsFWU", "aZk-k_OIXhG", "UxXchnQsb83", "QLkPGH-LYkF", "6IjNF0Eyqf3", ...	[ "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Dear Reviewer K1pa, thanks for you kind reply very much. We are glad to have this opportunity to address your concerns. We will continue improving our paper to make it better.\n", " Dear authors,\n\nThank you for uploading an updated version of the manuscript and an HTML file. The HTML file was really helpful i...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 7, 5, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 4, 4 ]	[ "QLkPGH-LYkF", "QLkPGH-LYkF", "6hKE4Voh6mo", "6IjNF0Eyqf3", "QLkPGH-LYkF", "UxXchnQsb83", "nips_2022_KglFYlTiASW", "nips_2022_KglFYlTiASW", "6hKE4Voh6mo", "6hKE4Voh6mo", "6IjNF0Eyqf3", "QLkPGH-LYkF", "QLkPGH-LYkF", "QLkPGH-LYkF", "UxXchnQsb83", "nips_2022_KglFYlTiASW", "nips_2022_Kgl...
nips_2022_wlrYnGZ37Wv	Sequencer: Deep LSTM for Image Classification	In recent computer vision research, the advent of the Vision Transformer (ViT) has rapidly revolutionized various architectural design efforts: ViT achieved state-of-the-art image classification performance using self-attention found in natural language processing, and MLP-Mixer achieved competitive performance using s...	Accept	Four reviewers provided detailed feedback on this paper. The authors responded to the reviews and I appreciate the authors' comments and clarifications, specifically that each question/comment is addressed in detail. The authors also uploaded a revised version of the paper. After the two discussion periods, all four r...	train	[ "JzsvoxPspUu", "PtNi56Ce1S1", "vcytZlC49Z1", "5SOiseeBCR8", "Jmr6X-hmg1k", "uE4MKBEvyBr", "HzVRTA9px-B", "v02LgXSwmKI", "9E2JNrrxZkX", "3Y_jBaO7gsr", "BR7MmAgezxJ", "EsmSLbo41JW", "BCUgzjlVL7", "h_kpfnBLW_X", "c6ypb13dnO4" ]	[ "official_reviewer", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the response from the authors. My concerns are mostly addressed. Although I am still worried about the throughput issue in standard ImageNet resolution, I lean toward acceptance as the successful trial of replacing self-attention with LSTM in ViT deserves credit.", " Thanks for your positive comments...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 5, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 4, 4 ]	[ "v02LgXSwmKI", "vcytZlC49Z1", "Jmr6X-hmg1k", "3Y_jBaO7gsr", "EsmSLbo41JW", "EsmSLbo41JW", "BCUgzjlVL7", "h_kpfnBLW_X", "h_kpfnBLW_X", "c6ypb13dnO4", "nips_2022_wlrYnGZ37Wv", "nips_2022_wlrYnGZ37Wv", "nips_2022_wlrYnGZ37Wv", "nips_2022_wlrYnGZ37Wv", "nips_2022_wlrYnGZ37Wv" ]
nips_2022_osPA8Bs4MJB	Delving into Sequential Patches for Deepfake Detection	Recent advances in face forgery techniques produce nearly visually untraceable deepfake videos, which could be leveraged with malicious intentions. As a result, researchers have been devoted to deepfake detection. Previous studies have identified the importance of local low-level cues and temporal information in pursui...	Accept	All reviewers are positive about this paper. Generally speaking, the proposed method is novel and is also easy to follow due to well writing. Also, the experiments are comprehensive. In the rebuttal, the authors also provide some qualitative results to clearly respond to the concerns of reviewers. So, I suggest accepti...	train	[ "NNvno0qQ25B", "j3TOg77SWjl", "NVe6S2N1xI", "BDEdZIairjt", "4OW5cyxmLwU", "MTiipQMwz4", "Mtt0wLxbTsn", "V2VKodwIWTM", "0QRUdzP29dP", "p3teEjcTMZ9", "zbbz1ew0FuN", "5Oo04rruNC8-", "HHN9S5nxl1ON", "G9wLvB4cNBW", "_BqXop1Au-y", "jo2urd0juA_", "JUqIE2pcn8Q", "KgHskORqAw8", "ul9Sk2FIv...	[ "author", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_r...	[ " Hi reviewer,\n\nThe discussion period is closing soon. Please take a look at our responses to your pre-rebuttal concerns. 1) Regarding novelty, we clarify the differences between this paper and related arts, where the key dilemma between robustness and generalization is resolved by the introduced low-leve...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 5, 5, 5, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 4, 4, 4 ]	[ "JUqIE2pcn8Q", "p3teEjcTMZ9", "zbbz1ew0FuN", "_BqXop1Au-y", "nips_2022_osPA8Bs4MJB", "nips_2022_osPA8Bs4MJB", "zAVQlCO2DrC", "zAVQlCO2DrC", "zAVQlCO2DrC", "ul9Sk2FIvVa", "KgHskORqAw8", "JUqIE2pcn8Q", "JUqIE2pcn8Q", "jo2urd0juA_", "jo2urd0juA_", "nips_2022_osPA8Bs4MJB", "nips_2022_osP...
nips_2022_MbVS6BuJ3ql	Maximum Class Separation as Inductive Bias in One Matrix	Maximizing the separation between classes constitutes a well-known inductive bias in machine learning and a pillar of many traditional algorithms. By default, deep networks are not equipped with this inductive bias and therefore many alternative solutions have been proposed through differential optimization. Current ap...	Accept	This paper aims at introducing a criterium for class separation. The paper demonstrates high performance, by proposing an affine transformation of the canonical embedding of labels, which lead to a maximal separation between those new vectors. Given the simplicity and good numerical results, I recommend accepting this ...	train	[ "mNjl8vJ2iqA", "gJmnMgirm4", "O7-jqKUpfcH", "IH_MvrJaxay", "nXyDOznw3Qh", "BcwjerF_FpR", "82MnAD7OhJb", "V1lT5wXHERc", "VRePyw72Ud9u", "Og87ZAxhqc", "0D1_NLqYv2Z", "yPm3kip21hv", "cZ1jwnDsIJK" ]	[ "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the response. I have no more questions, and I hope these suggestions can be useful when preparing a revised version.", " We thank the reviewer for their response.\n\nRegarding feature dimensionality, you can indeed set feature embedding to eg. $512$ dimensions with a standard softmax cross-entropy fo...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 7, 8, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 3, 4, 3 ]	[ "gJmnMgirm4", "IH_MvrJaxay", "nXyDOznw3Qh", "VRePyw72Ud9u", "82MnAD7OhJb", "0D1_NLqYv2Z", "cZ1jwnDsIJK", "yPm3kip21hv", "Og87ZAxhqc", "nips_2022_MbVS6BuJ3ql", "nips_2022_MbVS6BuJ3ql", "nips_2022_MbVS6BuJ3ql", "nips_2022_MbVS6BuJ3ql" ]
nips_2022_kcQiIrvA_nz	Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection	Deep neural networks (DNNs) have demonstrated their superiority in practice. Arguably, the rapid development of DNNs is largely benefited from high-quality (open-sourced) datasets, based on which researchers and developers can easily evaluate and improve their learning methods. Since the data collection is usually time...	Accept	This paper proposes a methods to verify unauthorized use of open-sourced dataset. The idea is to inject verifiable backdoor watermarks. The authors first show that existing backdoor watermarks can be exploited by adversaries for attacks. They then proposed novel untargeted backdoor watermarking techniques that are both...	train	[ "22JMt-5jpDV", "DYRzi32DHwT", "Mc13g0wBN0J", "YgPwpzn_Hna", "dogSr_xa9wX", "4R-oMjbbsAp", "fywNmFsKS3wq", "fTdLNGcv2R", "crzzszRL1p", "hHfuFYGTqmn5", "N9GwcFBj9Ao", "qPv0iys0-g", "J_Iv2zvxl8qt", "9vicxjS6K46", "i95KYOnJosS", "h6oQ97N-nOb", "UFbJ3K9pyXs", "k4paZC8xhMo", "D-iNlUn2-...	[ "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "author", "author", ...	[ " There are no ethical issues in my opinion. There are no ethical issues in my opinion. There are no ethical issues in my opinion.", " Thank you for your recognition of our discussions and kind explanations. We do respect your decision and are willing to wait for your final score after the Reviewer-Metareviewer d...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 8, 7, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 3 ]	[ "nips_2022_kcQiIrvA_nz", "Mc13g0wBN0J", "YgPwpzn_Hna", "fTdLNGcv2R", "fTdLNGcv2R", "fTdLNGcv2R", "fTdLNGcv2R", "qPv0iys0-g", "hHfuFYGTqmn5", "J_Iv2zvxl8qt", "i95KYOnJosS", "i95KYOnJosS", "9vicxjS6K46", "fR3qiUq7ISY", "D-iNlUn2-Y2", "fR3qiUq7ISY", "k4paZC8xhMo", "V1sGQYEAHvi", "9s...
nips_2022_F7NQzsl334D	ClimbQ: Class Imbalanced Quantization Enabling Robustness on Efficient Inferences	Quantization compresses models to low bits for efficient inferences which has received increasing attentions. However, existing approaches focused on balanced datasets, while imbalanced data is pervasive in the real world. Therefore, in this study, we investigate the realistic problem, quantization on class-imbalanced ...	Accept	After rebuttal, the reviewers unanimously agree that the submission should be accepted for publication at NeurIPS.	train	[ "QzOhALEf2wd", "PUvmtZO27gv", "J1L2F6N7W0f", "b-eMVSr-dkY", "y4rSUKj6Xgf", "T2zIWXr6gEO", "v6QhNSmN9nl", "wl0CDEcig3", "AxsK32u0SV1", "zgttOU_QLLN", "gWIFA1tKMh", "IKCeUCjrrdE", "uZKcq8FWI89", "18oY5L2-8gI", "PP3ESY3FlcW", "j-PDzOjdQZ2", "W7jtW_X8zpp" ]	[ "official_reviewer", "official_reviewer", "author", "author", "official_reviewer", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thanks for the detailed answer and the new quantization error results. I have updated the rating accordingly.", " Thanks for your detailed elaboration. I recommend the authors to combine the above content into the paper, since it can strengthen the contributions of your work. I do appreciate the efforts and the...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 5, 7, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 3, 4, 3 ]	[ "v6QhNSmN9nl", "J1L2F6N7W0f", "y4rSUKj6Xgf", "T2zIWXr6gEO", "IKCeUCjrrdE", "zgttOU_QLLN", "wl0CDEcig3", "gWIFA1tKMh", "gWIFA1tKMh", "W7jtW_X8zpp", "j-PDzOjdQZ2", "PP3ESY3FlcW", "18oY5L2-8gI", "nips_2022_F7NQzsl334D", "nips_2022_F7NQzsl334D", "nips_2022_F7NQzsl334D", "nips_2022_F7NQzs...
nips_2022_4F0Pd2Wjl0	Error Correction Code Transformer	Error correction code is a major part of the physical communication layer, ensuring the reliable transfer of data over noisy channels. Recently, neural decoders were shown to outperform classical decoding techniques. However, the existing neural approaches present strong overfitting, due to the exponential training com...	Accept	This paper is part of a popular line of research aiming to apply neural network concepts to the decoding of error-correcting codes. The main novelty consists in the introduction of an architecture based on transformers. The authors provide convincing and thorough numerical results comparing the BER and the complexity o...	train	[ "Km4WD5jxiXn", "BpfyE6OBR7Y", "V0E26lz5cBX", "E4njdxncOR7", "MsE6WVZOiIv", "q1vpEDDT5kI", "qsyu5hU9Xa", "zMMaItNd-X1", "h7TXKmjTNll", "i2n0exlmbhT", "YecrtciLAeq", "yL2lOIGjFh" ]	[ "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you again for the valuable ideas, which have no doubt helped improve our manuscript.\nWe would be happy to know if you are satisfied with our answers, or if there is anything else we can address.", " Thank you for the reply and the revised manuscript. I have read them and adjusted the score accordingly.",...	[ -1, -1, -1, -1, -1, -1, -1, -1, 6, 7, 7, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 4, 3 ]	[ "h7TXKmjTNll", "E4njdxncOR7", "nips_2022_4F0Pd2Wjl0", "yL2lOIGjFh", "YecrtciLAeq", "i2n0exlmbhT", "h7TXKmjTNll", "nips_2022_4F0Pd2Wjl0", "nips_2022_4F0Pd2Wjl0", "nips_2022_4F0Pd2Wjl0", "nips_2022_4F0Pd2Wjl0", "nips_2022_4F0Pd2Wjl0" ]
nips_2022_vgIz0emVTAd	DISCO: Adversarial Defense with Local Implicit Functions	The problem of adversarial defenses for image classification, where the goal is to robustify a classifier against adversarial examples, is considered. Inspired by the hypothesis that these examples lie beyond the natural image manifold, a novel aDversarIal defenSe with local impliCit functiOns (DISCO) is proposed to re...	Accept	In this paper, DISCO, a test-time defense against adversarial attack, is proposed based on prior concents of adversarial denoising, manifold modeling, and implicit function. The authors show promising efficiency and experimental results in DISCO. However, a large concern raised by some reviewers is the limitied novelt...	train	[ "f2ab6Yu6Ya4", "xTJx05aD7x", "Qx-RMNJ-rx9", "OCVuUVQN7v", "1GmX18t_r8O", "KHSgHBBtPgN", "Ud85DTzmTy4", "ak2l36xKZhb", "_PAtjxpA1IT", "6dv9nkAMWze", "WgsjHr4wL7B", "m642s8fS00g", "yzw041YJo-" ]	[ "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Dear Reviewers,\nWe appreciate your efforts in reviewing our paper. We have addressed your questions in detail. As the deadline is approaching, would you please check our response and acknowledge our rebuttal?\nThank you so much.\nBest regards,\nAuthors", " Thank you for the thorough response. It has adequately...	[ -1, -1, -1, -1, -1, -1, -1, -1, 6, 7, 4, 7, 4 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 4, 4, 3, 4, 3 ]	[ "ak2l36xKZhb", "KHSgHBBtPgN", "yzw041YJo-", "m642s8fS00g", "WgsjHr4wL7B", "6dv9nkAMWze", "_PAtjxpA1IT", "nips_2022_vgIz0emVTAd", "nips_2022_vgIz0emVTAd", "nips_2022_vgIz0emVTAd", "nips_2022_vgIz0emVTAd", "nips_2022_vgIz0emVTAd", "nips_2022_vgIz0emVTAd" ]
nips_2022_6rhl2k1SUGs	Watermarking for Out-of-distribution Detection	Out-of-distribution (OOD) detection aims to identify OOD data based on representations extracted from well-trained deep models. However, existing methods largely ignore the reprogramming property of deep models and thus may not fully unleash their intrinsic strength: without modifying parameters of a well-trained deep ...	Accept	The reviewers agree that the proposed method is interesting and yields good performance. A number of concerns were raised during the initial round of reviews concerning the rigorousness and completeness of experiments, but these were addressed during extensive back-and-forth between authors and reviewers.	train	[ "MFKTygbr2kF", "YOvmwWDqPe6", "8oJGA4TT3u8", "S_P8xvp0qd8", "1mvxr7LLXCe", "L3r7CEiNgw", "IYAd9rZzf_y", "GwShy9bg7YC", "jDM4sgM4xo", "iMQSsvedng_", "xm3bOit9_5s", "FUxiyzCb8Iz", "FO-kWtmDjbV", "qFl9vurc9Z_", "Zv-v1dOkmFn", "vThqHlEQTR_", "0Vqvr1OWuwcc", "au3MH8XUIUy", "BdegYlMim1...	[ "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "author", "author", "author", "official_reviewer",...	[ " Dear Reviewer WTn8,\n\nGlad to hear that your concerns are addressed well. Thanks for supporting our paper to be accepted.\n\nBest regards,\n\nAuthors of #1621", " Sincerely thanks for the constructive suggestions/comments of all the reviewers. We have correspondingly revised the current submission and marked t...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 8, 4 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 4, 5, 4 ]	[ "jDM4sgM4xo", "nips_2022_6rhl2k1SUGs", "BPD9S8oB4bZ", "iMQSsvedng_", "vThqHlEQTR_", "xm3bOit9_5s", "xm3bOit9_5s", "FUxiyzCb8Iz", "07-0TcR_qU", "vThqHlEQTR_", "bA_UWXls75g", "0BXWdZ-jPkk", "au3MH8XUIUy", "QRP8ENGCcmI", "nips_2022_6rhl2k1SUGs", "zGX08tJxYNB", "BPD9S8oB4bZ", "OujBX2wy...
nips_2022_bIlUqzwObX	Reinforcement Learning with a Terminator	We present the problem of reinforcement learning with exogenous termination. We define the Termination Markov Decision Process (TerMDP), an extension of the MDP framework, in which episodes may be interrupted by an external non-Markovian observer. This formulation accounts for numerous real-world situations, such as a ...	Accept	All reviewers are in agreement that this paper should be accepted. It combines clear writing, a well-motivated setting (external termination due to unobserved accumulation of costs), and sound theoretical analysis with a novel algorithmic contribution (TermPG) that performs well on an interesting domain that aligns wel...	train	[ "ghIE9_xi6Fi", "O9wi3iwn1LV", "O1jyfgSLxF5", "XOlz6thldNB", "aFLtkU-mNMX", "BkDB8f7xiE", "bYboBHxnT6v", "iAsE8EDZaoz", "oHyn8BqxDbe", "_MfTwYZxSUh", "d1D-syiasit", "3FGwXNnlrv5" ]	[ "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " I thank the authors for their detailed response. I encourage you to make the changes & clarifications discussed. I recommend acceptance of the paper.", " Thanks to the authors for their response and clarifications. I've read through all the other reviews and responses, and am satisfied to recommend acceptance...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, 7, 7 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 4, 3 ]	[ "d1D-syiasit", "XOlz6thldNB", "iAsE8EDZaoz", "aFLtkU-mNMX", "3FGwXNnlrv5", "bYboBHxnT6v", "d1D-syiasit", "_MfTwYZxSUh", "nips_2022_bIlUqzwObX", "nips_2022_bIlUqzwObX", "nips_2022_bIlUqzwObX", "nips_2022_bIlUqzwObX" ]
nips_2022_p_g2nHlMus	Rethinking Generalization in Few-Shot Classification	Single image-level annotations only correctly describe an often small subset of an image’s content, particularly when complex real-world scenes are depicted. While this might be acceptable in many classification scenarios, it poses a significant challenge for applications where the set of classes differs significantly ...	Accept	This paper tackles few-shot learning with a transformer architecture and, inspired by the intuition that fine-grained information is ignored in existing methods, uses an inner-loop token re-weighting method to improve results. Overall the reviewers appreciated the use of modern architectures (Vision Transformers), th...	val	[ "FoJbLjv1q4p", "xed_i8L6fo", "yfGwk4qBB-H", "Ihh3_GbsB2S", "WiNslw0VrUP", "jSGLAMzN_A0", "8iDmcnOT_Vj", "-cn33EhWxD", "fZkjysigkyP", "6R2dlUKR48i", "awuPyh8j9s-", "dDhOVIcpwNF", "A9HFNo0-M3c", "v6SSYysrYfX", "KCdhzm_i_c" ]	[ "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for your continued feedback!\n\n> _[...] for the supervised pre-training for the same FSL task in Fig. 4, what exactly is done?_\n\nFor adequate comparison to related work in FSL, we follow the widely adopted pretraining scheme used in FEAT [52] and other works (e.g. DeepEMD [53]) for our supervised pre...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 6, 7, 7, 5 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 3, 5, 4, 5 ]	[ "xed_i8L6fo", "8iDmcnOT_Vj", "awuPyh8j9s-", "-cn33EhWxD", "fZkjysigkyP", "8iDmcnOT_Vj", "KCdhzm_i_c", "v6SSYysrYfX", "6R2dlUKR48i", "A9HFNo0-M3c", "dDhOVIcpwNF", "nips_2022_p_g2nHlMus", "nips_2022_p_g2nHlMus", "nips_2022_p_g2nHlMus", "nips_2022_p_g2nHlMus" ]
nips_2022_--aQNMdJc9x	Misspecified Phase Retrieval with Generative Priors	In this paper, we study phase retrieval under model misspecification and generative priors. In particular, we aim to estimate an $n$-dimensional signal $\mathbf{x}$ from $m$ i.i.d.~realizations of the single index model $y = f(\mathbf{a}^T\mathbf{x})$, where $f$ is an unknown and possibly random nonlinear link function...	Accept	In this paper, the authors study the standard phase retrieval problem, in the case where the signal is assumed to come from a generative model prior. In particular, they propose an algorithm that starts with a spectral method followed by an iterative approach. The authors provide two theorems giving guarantees on the p...	train	[ "9EhSYHamwA6", "2YnOsXRc8mH", "K_GYClagkMr", "xVGHx7K9REz", "4PfuxtXc2Sa", "E4FeSgD-53y", "NAdEREDnZxZ", "7-74ZXBWMrc", "jgyU9ZueFcS", "qYOA7I0tli8", "wUN_QqPkOrt", "miOX_i6vhL", "7aHXDd-oStf" ]	[ "author", "official_reviewer", "author", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " We are pleased that the reviewer found our answers globally satisfactory, and we thank the reviewer again for the comments. Our responses to the two points are as follows:\n\n(Comparison with the Bayes-optimal performance) This is a helpful suggestion. We will compare the performances of our algorithm and the...	[ -1, -1, -1, -1, -1, -1, -1, -1, 5, 6, 6, 5, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, 3, 3, 3, 3, 3 ]	[ "2YnOsXRc8mH", "K_GYClagkMr", "7aHXDd-oStf", "miOX_i6vhL", "wUN_QqPkOrt", "qYOA7I0tli8", "jgyU9ZueFcS", "nips_2022_--aQNMdJc9x", "nips_2022_--aQNMdJc9x", "nips_2022_--aQNMdJc9x", "nips_2022_--aQNMdJc9x", "nips_2022_--aQNMdJc9x", "nips_2022_--aQNMdJc9x" ]
nips_2022_V_4BQGbcwFB	Positively Weighted Kernel Quadrature via Subsampling	We study kernel quadrature rules with convex weights. Our approach combines the spectral properties of the kernel with recombination results about point measures. This results in effective algorithms that construct convex quadrature rules using only access to i.i.d. samples from the underlying measure and evaluation of...	Accept	We thank the authors and reviewers for their work throughout the reviewing process. The paper generated detailed and interesting discussions. While there remains minor concerns, we are confident that the paper brings new elements and will generate exciting discussions in the kernel quadrature community, and we are happ...	train	[ "YubQrGn7tqp", "nIYRJNJ6eR4", "9PXbD-OCEpg", "_0xSQ3bowK", "z-m1FoRRkqT", "vz6fs5Sq24c", "AUd1FDFU8n", "nqQZ6Hk57OV", "Uct1aPwY-Hx", "Q1zT_ndtZy5", "CKquFpF2P-O", "lXO6x6hAijt", "uHM8oC9Eb_m", "Eaxwvp3MNXx" ]	[ "official_reviewer", "author", "official_reviewer", "author", "official_reviewer", "author", "author", "author", "author", "author", "official_reviewer", "official_reviewer", "official_reviewer", "official_reviewer" ]	[ " Thank you for the response. I will keep my original score.", " Thank you to all the reviewers for constructive comments and suggestions. Although we have already replied to each reviewer, we here summarize our primary updates of the revised manuscript in two parts:\n\n- Contribution and Limitation: We have ad...	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 8, 5, 6, 6 ]	[ -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, 3, 4, 3 ]	[ "Q1zT_ndtZy5", "nips_2022_V_4BQGbcwFB", "_0xSQ3bowK", "z-m1FoRRkqT", "nqQZ6Hk57OV", "Eaxwvp3MNXx", "Eaxwvp3MNXx", "uHM8oC9Eb_m", "lXO6x6hAijt", "CKquFpF2P-O", "nips_2022_V_4BQGbcwFB", "nips_2022_V_4BQGbcwFB", "nips_2022_V_4BQGbcwFB", "nips_2022_V_4BQGbcwFB" ]

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