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In this paper, we formulate a multi-round extension of the PM framework in which each party can perform operations over an ordered sequence of quantum nodes, assuming standard causality locally but not globally. The formalism is analogous to the PM formalism, except that the local operations are now generalised to quan... | i | 389a5fc1b0998699dcbd46a382b7be87 |
In this paper, we address this issue by considering the thrust event shape for which we are able to obtain precise theoretical predictions from analytic higher-order resummed calculations, which can be used as a benchmark for parton-shower predictions.
An extensive survey of parton-shower predictions as carried out in ... | i | 1a672d23dc0ef62f0c3f2ee20c393503 |
(where {{formula:58a0b573-acb2-4e2a-b7ee-eaeaf5dac1c2}} , {{formula:1062c350-0228-4f49-967d-a2cfba550c41}} , {{formula:e373d2db-43fc-4306-95e1-b41123aa8f0d}} , {{formula:aecdd85c-51ce-4cc2-a77d-43426c376140}} are cosmological parameters whose values are adopted from the latest Planck results {{cite:cce90baf45d5975011e... | m | ea3d58fe5f3b8fd73e8442eb1ee94ddf |
Varying the number of classes helps. It is striking how much more accurately the ImageNet-X family is able to represent the diversity in APRs present in our dataset collection, compared to just ImageNet by itself. In cases where it is not possible to test an architecture on a variety of different datasets, it is thus a... | d | 9381dcbfe82b5ec9dfefa23849b0ab4e |
The model assumed in Figure REF is the established PBC benchmark {{formula:e27d2e8b-c51b-40a8-83be-b12a23fb8047}} {{cite:e7052597cd84c396b640adfdab3009822dc1e904}} that we repeat here below for convenience.
| r | 61a5e118e78455d8aae22bf3f2f13988 |
LSTM: Previous work by {{cite:71ee0e6e5661c2820d4deb3871bcc523486d4de9}} used textual features to estimate the presence of a complete set of objects in a text segment. We adopt their architecture, representing documents using 100 dimensional GloVe embeddings {{cite:ed72850883dc51f3c6b58d9c3bd441ab82ce7abc}}, and proce... | m | 072e18bf4f2aa803fc56615cbfb24462 |
The governing equations (REF ), (REF ) and (REF ) are solved numerically using a pseudo-spectral method that transforms the field variables into wave space. Specifically, Fourier series are used to discrete the variables in the homogeneous directions (streamwise {{formula:ae80bf57-eb3d-4452-b391-d3894b4dc54b}} and spa... | m | a96cec6713c737e7e162ba63dd13fa3b |
The theory of dynamical systems emerged from the need to predict the asymptotic behavior of solutions of differential equations. The field of topological dynamics (and the Conley theory {{cite:42f339a65797fbacc68d3303057b9ae291621f5f}} in particular) has developed tools for analyzing the structure of invariant sets, or... | i | 0fa5c604f71733edb376ea5f5007054a |
While we have demonstrated the principle of a tunable quantum-enhanced sensor, it is worth comparing its performance with existing matter wave gyroscopes to see if any advantage can be gained. Free-falling atom interferometers represent the state of the art in atomic inertial sensors and, in such a device, a sensitivit... | d | 8ae4ce7731bcfc61f380b3d09cf79e3c |
Additional constructs have been proposed that may address some of these concerns or advance the state of fair ranking in other ways.
{{cite:dc7670b7a95826c596882515cec7be4f891ee511}} present a pairwise definition of rank fairness that may be easier to apply with missing relevance and/or group membership data.
It requir... | d | e63abcaf80bee60cf5d37f84ebd411d0 |
The displacement of the object can be calculated by Eq.(REF ), and then the displacement of the current frame can be determined. At the same time, four binary Fourier basis patterns, one Hadamard basis pattern, and the corresponding five single-pixel detection values are obtained for each frame which could be used for ... | m | 3f8838fe4c914c9740e0af96636fb0f9 |
From Kepler equation, one can get (one can see {{cite:364b2362add7c1c65298ed9ff77f5ee9d0c4a121}}):
{{formula:8ed8d9e6-035d-4e76-a26d-aeb00020b7bc}}
| r | 9a6e310b7b806b8186682a75a1820f2f |
Further, we say that {{formula:41e5c387-a7cc-4645-9044-dbb48c9f99f8}} is subdifferentially continuous at {{formula:8b22c8f6-3008-4c57-b5cf-51fd1f5112e0}} for {{formula:451593ac-5571-4a59-a77a-9b23b589dca4}} if for any {{formula:47af298e-da27-4248-89a1-1bc1a236e788}} there exists {{formula:6f812de5-92d4-473a-a427-0b... | d | 135ad6b4a70ad5241932e4fb170088b4 |
The large-scale solar and galactic magnetic fields are generated by a combined action
of helical turbulent motions and large-scale differential rotation due to the {{formula:38757df0-2406-4d17-90b1-323c3e4f82a2}} dynamo
{{cite:4a8ea9dc18cb6584363052292d615c5a26f06316}}, {{cite:9a962ae92a1a91a935684de26e39322d459cd5eb}... | i | 1fda2086414f93c999cdd3db1c0f80b3 |
Since our framework trains a classifier using self-labeling, extracting the right representation of the data sample is crucial.
However, most of the feature extraction methods have difficulty with handling a dataset bias {{cite:091be79be571081f6608de16097af0a71535b2d9}}.
As future work, we will focus on the disentangle... | d | eb1c9b9f1da3968db9d776a39c8d4536 |
We have considered the regularization of applying the quantum extremal surface prescription to gravity theory with matter fields to the Schwarzschild black hole metric in {{formula:ec7f65ae-39d8-4671-b69e-e339b051ca43}} using thermal coordinates {{cite:0a81cea81a9d87a95d60b43e8be3855c996a93da}}. This consideration per... | d | 37ce3438ea1627f5c2f4d2f9f12305e6 |
which is a discrete analogue of the constraint equation {{formula:737b6bd5-231e-4fc1-8349-06fe28194f53}} in the smooth case {{cite:2bc54cbdbdd17478e0a0318ef1e4b77bb30f7bf3}}, {{cite:b71ec8dbc7b19f81bb6b734b0ee43782d3e2c69b}}.
Following Kazdan-Warner's arguments in {{cite:2bc54cbdbdd17478e0a0318ef1e4b77bb30f7bf3}}, the... | r | a15c07135caa9c354f1bd148537f6a52 |
In linear-chain CRF {{cite:8e4dad58608433f9e52df2dd43ab7bee28ab1a43}},
partition function can be accurately and efficiently computed with
the Viterbi algorithm based on dynamic programming.
However,
in seq2seq networks,
outputs at each timestep couples with each other,
and can not fit into the framework of the Viterbi... | d | da9a313479aaf26d865ff8b71d93269c |
We use the standard wav2vec 2.0 BASE architecture which contains 12 transformer layers, and use the publicly released pre-trained checkpoint from fairseq {{cite:cd087fe7bc18276832ebba3c7effd70a3c8a3b93}} which has been pre-trained using the LibriSpeech {{cite:43c1d6f9548d3d0d0443c647eff6b46249aead46}} dataset. We use a... | r | 6764b48285098cfcff64c6a1c93e05fc |
We compare AR2-{{formula:3e84380a-7f80-4455-af24-b928d4e5de88}} with previous state-of-the-art methods, including sparse and dense retrieval models.
The top block shows the performance of sparse retrieval methods. BM25 {{cite:5094501eb59353910d77c60b1e765f6418ad112d}} is a traditional sparse retriever based on the exa... | r | 5de0394711bae2887b9d868eb8f1a419 |
Table REF shows the results of CaDDN on the KITTI {{cite:178ff8eb7eb9b1e83583bd302c85907bb040632f}} test set for BEV detection. Our method outpeforms previous single frame methods by large margins on {{formula:0b343f7d-6afd-47a4-810f-766020f63dca}} of +2.91%, +1.59%, and +2.22% on the Car class on the Easy, Moderate,... | r | af65dc1515cd981330240284a61408f7 |
In this section, we report audio-visual synchronisation results on the VGG-Sound Sync dataset consisting of videos with general sound classes,
and compare with several strong baselines.
Results are provided in Table REF .
blackFirst, while comparing with the recent AVobjects {{cite:3420b5574475229470d3073c561903761012b... | r | 84ba518f4b07203d03138df58136e208 |
Let {{formula:8af0c375-8a63-4a0e-a059-e5a735b02213}} be the truncated OLS estimate using {{formula:a9493f7c-7ce0-4bbe-a78a-b02486bbbcdb}} , on a dataset {{formula:6d7abae6-04ce-41e0-a8e8-0c1b22213e45}} where {{formula:f1079621-327e-4e14-a89e-f78d4c5ab353}} . Then
{{formula:a78bf26b-71ec-46a5-b5eb-66625af0d34e}} {{ci... | r | 6dca5fa558251e462c24b0829cad486d |
We presented a meta-learning approach to extract the inductive bias of differentiable supervised learning algorithms, which we hope will be useful in normatively interpreting the role of features of biological networks. This approach required few assumptions beyond those that make the inductive bias an interesting way ... | d | f12d15364825ec095f2e55fa5992199f |
where {{formula:37da87ed-4bc7-46e0-842a-3974045ea3fd}} and {{formula:e7627f39-f5aa-42a8-84ae-97a49a1651a6}} operate on the two input modes while {{formula:9da9441d-c07d-483f-a0fd-d1b89aed7467}} operates on the SH-mode and where the parameter {{formula:1fbce1ed-d19a-4eac-be06-aa8c43f07f8b}} is a coupling constant pr... | i | 6cc08bbc891fc853b59fd6f1cf9d0765 |
The MAE models in Table REF are pre-trained for 1600 epochs for better accuracy (Figure REF ). Even so, our total pre-training time is less than the other methods when trained on the same hardware. For example, training ViT-L on 128 TPU-v3 cores, our MAE's training time is 31 hours for 1600 epochs and MoCo v3's is 36 ... | r | fd865b141b713e2d1f5dcc21f2b3afb5 |
3. Find more general solutions different from (REF ) of cone holography. Similar to the case of wedge holography {{cite:3c11b24417d6ff3023c9c9f6dbfb25d478a5d9a3}}, these solutions are expected to reproduce more general Weyl anomaly, such as the second and third terms of ().
| d | 7032f795c20a5e22349d8ba6ad59ae4c |
It should be noted that this is an orbital dependent, non-variational method, which is applicable for both ground
and excited states. The nagging orthogonality requirement of a given excited state with all other lower states of same
space-spin symmetry is indirectly bypassed. In this way, while {{formula:84d98404-22e2-... | m | 5eba0ddc323c43bd4586e71f0278ecfe |
For all {{formula:7dcc30b7-2630-4f28-9b21-41275bdf24a7}} , {{formula:85439906-7871-4829-9fbb-de858e2570f3}} . This is because {{formula:526b0f39-026f-4d19-8eec-ab69305a46db}} from (i), and thus
{{formula:179bafe1-481d-4081-a9ad-2e7f002601af}}
Lemma REF below states that with high probability, each community contains... | m | d2c16cbd81d52b6e6375a8beed9b5d4f |
Even though the Laplace method is very efficient, it can be quite
inaccurate since the
Gaussian is fit at the mode of the intractable posterior density.
With Variational Bayes methods, one main disadvantage is the
assumption of a simple factorization of the joint posterior, usually
into independent marginal posteriors ... | m | b4c36a81ac8faa841054d42ace1f64e1 |
The dynamics of classical homogeneous Yang-Mills color fields
and its chaotic properties have been investigated and well understood
about 2 decades ago (see e,g {{cite:d8ccd15edbbcd3806f6f3e078e964c634f28f7d8}}, {{cite:ac6475528ccc90f66d8ee5f34b44b0d39e1f388e}}, {{cite:7f5d39b89a02e05a7c3533bf0c35e4754a79517e}}, {{cite... | d | 6e9fe3b3d4126b8b56252ae21304a8cc |
We release video results https://youtu.be/z-rBcY87XCw on test sets of cityscapes dataset {{cite:60ae7e81b1851ef09195ddaa5da2d148ed3bcbc6}}. Our method shows much clear and consistent prediction compared to state-of-the-art image UDA method, confirming its robustness and effectiveness.
| r | 0b945371b0da7fb8812e7e751f241de1 |
We compare LongT5 with various top approaches: BigBird-PEGASUS {{cite:7efb0bf9a6bbe69af665c70899f1365fc5a12c30}}, HAT-BART {{cite:6dffbe0380062fd1bf0c27a2ec5cd702126c6965}}, DANCER PEGASUS {{cite:0dc95dcdc3a09ba82f10099c5a432f6deb87eb27}}, PRIMER {{cite:77d155e734234c300e914c40a1c6d27b7af77955}}, TG-MultiSum {{cite:048... | r | 85e54593636dc1b23f379c02f470abde |
Table REF presents our results of training from scratch on the Kinetics-400 benchmark. Comparing to the R3D-50 baseline {{cite:889d18c62979f7c63884bcf803e779e7474709b8}}, the modern training methods and architectural changes introduced in R3D-RS-50 significantly improve the top-1 and top-5 accuracy by 3.8% and 2.7%, r... | r | 96c87128511aec4716fa96cdbd3539d8 |
Theorem REF completely classifies cohomogeneity-one shrinking, expanding and translating solitons, and cohomogeneity-one special Lagrangian cones. However, there exist cohomogeneity-one special Lagrangians in {{formula:3f2cb205-2b25-4588-ba5e-7d969ef86c06}} that do not lie in the zero level set of the corresponding m... | r | eba6b4c2d082a4973c3e2e428a79fee1 |
Because we have {{formula:cdc92c3e-a1fe-45ce-9262-833a61d4232a}} ,
{{formula:7ff6a61d-8d26-438f-9355-a633d92db6f3}}
is equivalent to
{{formula:a5a6c54f-94d4-441f-9d6b-afc7e2cd6ce9}}
where {{formula:ee074baf-3c1b-4aa2-a742-ad50087f6084}} denotes the standard half-Cauchy distribution on positive real with a scale para... | r | 8c00e0b4df3e1cf2a691ba630ccb8694 |
In this paper, we reviewed a collection of data integration methods in causal inference.
A common perspective views data integration in causal inference as a missing data problem where the study sample is a subset of the target population. This problem is referred to as generalizability or verify-in-sample. We summariz... | d | 5cdc8ee69459526e98db3bd0c043043a |
with parameters {{formula:90ac64cb-87a1-4c1e-ba2a-c85decf74297}} of the deep model {{formula:edc251aa-3267-4ac8-b7b0-7fddee9ef8b7}} .
The posterior distribution in (REF ) is generally intractable and therefore, the integral can be approximated by summing Monte Carlo samples obtained from {{formula:4e6427e3-23d1-47c7-8... | m | bbcfa8692c4491d89ea52253a9a0fefe |
In this subsection, we explain the difference of PPConv from other methods in detail. Primarily, following our design goal explained in Section , PPConv utilizes 2D convolutions to efficiently extract local features, unlike voxel-based or point-based methods. Projection-based point convolutional networks proposed in so... | d | 0e2726eb905b32397c634dee73914a17 |
The results are shown for four qubits in Fig. REF and six qubits in Fig. REF . The effectiveness of a classical optimizer for VQAs is typically only assessed by the convergence rate of the cost-function without taking account the quality of the output circuit {{cite:d6048e7e2460edc8df06055eed902c3fb74a9eee}}, {{cite:f... | r | 8d818396764000e606bacd0ab629b55f |
Our analysis relies on the contraction of hidden representations in total variation stated in Assumption REF . As discussed in Section , the standard Doeblin's condition is sufficient for the contraction {{cite:a00b71ea7e84504d8f5e19432d8b66c790d1eaf3}}. We conjecture that it is possible to prove Doeblin's condition fo... | d | 5bd6603d143eed0c035f43880a83a715 |
Cryptanalysis promises to be a very fertile field for
developing insight into the quantification of computational resource needs.
A game theoretic view of cryptanalysis was introduced by Von Neumann and
Morgenstern and later taken up by Shannon {{cite:689f3d01cc348d05fdf881e2703604e5644bcc15}}, {{cite:4e094f62af0debc6e... | d | 90c2fe1ba42b4f074f2dd5fdc9b8faf6 |
Let {{formula:2f139d80-4c87-42dd-b6dc-08920960057d}} denote an image of an object, and {{formula:6f5d7e40-36cd-440b-98d7-702e6ba28d92}} denote pixel coordinates.
The goal is to learn a function {{formula:b56cb775-dcaa-4707-a778-3c53ad00bb04}} that outputs a pixel representation at spatial location {{formula:44e7e8db... | m | 95fbd642bfc16cbb4cd5d2780b500fd9 |
Online harm {{cite:d76bda52b414ebd6b4d4883c5d57049efc484afc}} and—particularly for Natural Language Processing (NLP)—abusive language, are highly complex phenomena. Their study spreads across several subfields (detection of hate speech, toxic comments, offensive and abusive language, aggression, and cyberbullying), all... | i | e7ffcefa0bd7952514125a6b8ec8cb44 |
As is known to all, the real-variable theory of
Hardy space {{formula:1c21294d-7d16-4d42-b028-14dda5e27740}} plays an important role in various fields of analysis and PDEs; see, for examples, {{cite:04bbcf3cfcf419697d96cbf9e3469f328bb2361d}}, {{cite:83262c4674d2072f1620f06263095c830c2cf6a9}}, {{cite:30db93a9f6641f2... | i | f5a877d2015d900d7fa88acd6d0225d5 |
We study two main on-device DL frameworks, TensorFlow Lite and PyTorch Mobile, from Google and Facebook, respectively. We use image classification as a common DL task to evaluate the robustness of the frameworks. Our controlled experiment is designed to study the effect of the models, the adversarial attacks, the quant... | i | 18e2bb1e3c72df05d573a03edec67adb |
It is also noted that other machine-learning methods including k-nearest neighbour regression (KNN) {{cite:5305aee062ae27921042a86aff58732480313d96}}, least absolute shrinkage and selection operator (LASSO) {{cite:f43a481607798c0a8e85a770737c9e4a95624d9b}}, neighbourhood component analysis (NCA) {{cite:b6207956d7b36691... | r | bd0c0913a603ed1cc1ce8f011d790f24 |
is equal to zero. Hence, one can identify {{formula:dcf750d0-9707-41f3-8154-f3e39e5fe53d}} by averaging the predictions {{formula:e0439b8e-ff26-4b67-a18e-4a22101121f2}} made in the complete cases over the distribution of {{formula:dbb9291d-b352-4066-9362-17d90a6a46d5}} in the full sample. More generally, under the M... | m | 524717df8bea316343637b3b127fc606 |
Most semi-supervised learning methods assume that the labeled and unlabeled data come from the same distributions {{cite:3a30f18ad8ef15b00218da29cc4697d5f9854b0c}}, {{cite:39337b951aa30acae95f1bbe2a1cecd78b53475a}}, {{cite:3f291fbe6f86e3fffe5fd7f35411493dbe4281a0}}.
In other words, the subsets of the data are labeled s... | i | c848e9cc81e101f0fff3c12aa7189d8b |
Though the stochastic gradient method is popular in practice, it has well-documented deficiencies.
Notably, the method is highly sensitive to algorithmic parameters, with small misspecifications often drastically degrading performance. Recent works {{cite:a6d2ec9301f2906f9555ea69ea406e630098c516}}, {{cite:d10328867066a... | m | c2ba72dd665da08a6d623b377efc5b4a |
First, a YOLO-inspired {{cite:86e7c75fa2aa3208ad4d65ff38f7d93fc38d6e97}} input layer is added, consisting of a 7x7x7 convolution with stride of 2. In Figure REF we mark this particular layer `A'. This input layer quickly reduces the size of the volume being processed by the network, while preserving a wide field-of-vi... | m | 5dcd8610e550550aed3c5c7a4cb7b7d7 |
In our comparative analysis, we consider the following optimization algorithms:
SGD, RMSprop {{cite:c81b9bb8454d260e5e01dca5fd1339698e3e3a85}} and Adam {{cite:f66ff58272d7cb8e9d232a8a992c5f383980e612}}, Entropy-SGD (eSGD) {{cite:d5d9479f2810054107a018e117a644256b33ef0a}}, Accelerated-SGD (aSGD) {{cite:30ceddb4753f8bb0c... | r | 11757c861ec7fcc8ab7d586f5406fb34 |
13) It has been argued that OJ 287 may produce a few muon neutrinos with energies more than 100 TeV in instruments like IceCube-Gen2 during ten years of Fermi flaring epochs, influenced by the modeling of the 2017 flare of TXS 0506+056 {{cite:12ca3b0a803edc3f1e402aba6f52193e12b43b80}}, {{cite:4d2bfed486a5ad2c1dfba40e9a... | d | dc0d7441bbdbcede134aef0e52c25cc1 |
The past decade has seen an impressive growth in the development and application of machine learning techniques {{cite:f8f1d62eb274a6f252dfe5b855c8a2dd0349951a}} in quantum chemistry and computational condensed matter physics {{cite:e94c6446df77590db7283f3f284b6a4b3512efe1}}, {{cite:192f2cf5e79b6db19bb56f24ebb4cf4df139... | i | d49fde67718f3342acd00b016e67b7c1 |
Model:Optimizer
We use the Adam optimizer {{cite:e291f5ffbb9f9a86cc0be3ff60c9015601651047}} with: exponential decay rates for first moment estimates {{formula:0540efb8-2a7e-4c5c-88b7-f6838a673f17}} , second moment estimates {{formula:1803ac9c-d861-4a1f-a812-d58d267ecc48}} and {{formula:a1ff2e81-07e2-4381-ad96-bac98a4... | m | 6a8f5cb7d0323ce7ed6ab4c07340805c |
The amplitude of the breathing motion depends on both {{formula:7473d2f0-bf34-44bf-b910-386228b1af8a}} and {{formula:af0b97b1-b5c4-4fd9-83f2-49c287bd0e60}} . The spiral density waves could drive alternate expanding and compressive motions along the Galactocentric radius near the plane ({{cite:efd25d9d30bd3e4b01c6fa1f7... | d | b62765845cea370696aaa6bb5dbf2941 |
The following result can be proved using the same ideas as in Lemma 8.2 of {{cite:4e7052764bfad7abc2f4a5c456b196b6ec764cef}}.
| r | f779197778b1f0d6f1628dc16f31b2a5 |
As described above, the full noise model we use involves two noise parameters, the noise variance {{formula:5f06b946-6319-4790-9c35-50a93fd51ec1}} and the swap-out probability {{formula:457671ad-1ba8-4714-bb35-2c8a41293a26}} ; the error threshold is a line in {{formula:5f33e0bb-a2b4-4187-b8cf-d28d65df8674}} parameter... | r | c947ee803efc6486209b57c8d83683a1 |
Numerous extensions to the proposed approach can be considered. One argument for simulation-based design is the ease with which sensitivity to model assumptions, such as the value of nuisance parameters, can be assessed {{cite:f7a46a4e94dc7023e6b63da7403033e0a3c5da7b}}. Future work could consider how a systematic asses... | d | 1ade9edd84180827fa018e352eeebbc7 |
As shown in Table REF , for both datasets, MARK-Task outperforms all competing methods in terms of average accuracy, while showing no sign of CF (BTW is close to zero). This is specially remarkable for Mini-Imagenet, as competing methods use complex AlexNet-based architectures during training versus our simple convolut... | r | 5eefd8c4090c08b4c3caaa5b903a6b4d |
Neural Networks are a widely used tool nowadays, despite the lack of theoretical background supporting their abilities to generalize well. Classical notions of learning guarantee generalization only if there are more examples that parameters. It is clear that a stronger assumption is needed to achieve tighter bounds, a... | i | e83338e2230a591e78b55a603f1684f5 |
The rating-based prediction method aims to learn latent factors base on the rating matrix between users and items. The most common rating-based methods of the recommender system are Factorization Machine (FM) {{cite:42be4fed519886509e668ed0c2505af2e9b92d4b}}, Latent Factor Model (LFM) {{cite:e8368b2f4481e6706e391b0bd8f... | m | 3b1d4b9efde8e37b9785cbc06d9daacd |
Fig. REF compares the performance of U-Flow and C-Trumpet. The experiment shows that U-Flow significantly outperforms C-Trumpet both in posterior sampling and UQ. Table REF gives a quantitative comparison of U-Flow with baselines, including the basic U-Net {{cite:0762e959025549f2ac6900a90fba640c502afbf2}}. U-Flow exh... | r | 6446301fe176cbc71cfb1f55305f8792 |
As evidence, when we are studying the stability of the network in {{cite:68318c20e73df64108c8fed7fa4c26272f9a2193}}, we find that without limitation of entropy model (imagine setting {{formula:6880d434-e27d-4155-be7b-50d6b87558d0}} to {{formula:19c74df4-3d51-4c58-bb57-003c7746553f}} ) and quantization, {{cite:68318c20... | d | 1d85a51b7fa935d8c69c17444e8adfc7 |
In the graphs, we have highlighted the temperature points corresponding to the beam energy values used in BES. To get these temperature (T) and {{formula:8646136d-322d-4d4a-bfa9-33efa1afaccd}} from the value of beam energies ({{formula:df1ed8dc-97d8-4907-b6a7-a58065c284c9}} ), we have used the following expressions, a... | r | f851a991811936edc40a6acb0d61136f |
First, we compare our RDN with several state-of-the-art gradual SR methods: DRCN {{cite:8de05db60d73231b2294ca51e28d9316b8030d3d}}, LapSRN {{cite:679ea3d227b45102202dfc82682627dacd347ce9}}, DRRN {{cite:eb475132bc6bf798d2e10a2a881de26079fa2e0a}}, D-DPBN {{cite:e5bcbec090eac1e872bdc8b8df7ada915651b653}}, and SRFBN {{cite... | m | 26dcaf5180a17a9dbc82645763eea2f6 |
Speeding up gradient based methods has been a subject of interest over the past years with many practical applications, especially with respect to Deep Learning. Despite the fact that many optimizations have been done on a hardware level, the convergence rate of very large models remains problematic. Therefore, data pa... | i | 3e63e7e625eca1e5ca6acbd130e52127 |
Despite its structural simplicity, we demonstrated that MIAN works efficiently across a wide variety of MDA scenarios, including the DIGITS-Five {{cite:ad1e0673d9f5af15432397606905eb57eaa91be9}}, Office-31 {{cite:59eaa26cb64a0ca58a0c088d1a878f1f0ed5f7b5}}, and Office-Home datasets {{cite:48f27cb205aaa3d0d9d768d175de894... | i | caf5aa3667cb007b3a8e88bbd563e20e |
where {{formula:02f97c80-8ad3-4be1-b93f-6fb6866483d3}} is the returns on the {{formula:0f471c3e-bd0b-43c8-8b85-953eea5d431b}} -th portfolio of Fama and French's 25 benchmark portfolios at time {{formula:70d9b133-7644-491c-ab5a-2f8546542627}} , {{formula:0a6d12ce-d9ba-44b1-b8d4-7cdd31208777}} is the risk-free rate at ... | m | 900b4ecad09259f98a81812e74784ae5 |
Although, as we have just seen, these problems are all decidable for automatic sequences in theory, in practice, the automata that result can be extremely large and require a lot of computation to find.
We can use Walnut, a theorem-prover originally designed by Hamoon Mousavi
{{cite:26ff11624786c8fc7a4a5500d0cddbe7fbaa... | r | 9433e088d3b41c06d4a0ca4ec08b0f31 |
Figure REF shows a retinal vessel segmentation results using the proposed method. It shows that the proposed method is able to properly segment thicker vessels, which similar as its respective ground truth. However, in some cases there are few discontinuities observed in the segmented thin vessels that is the limitati... | r | f4537357a18051cd591ca3154932a0d5 |
On the other hand, more structure is present in a system of many degrees of freedom, such as a metric.
One can probe several features of a system by following a metric approach. But such a choice of a metric is not unique.
And a symplectic structure always induces sets of almost complex structures on a symplectic manif... | d | 5a24c0e549cff320905be8b0ae0828a1 |
We tackle this challenge by first making the following observations on why emergent communication is difficult in a decentralized multi-agent reinforcement learning setting. A key problem that prevents agents from learning meaningful communication is the lack of a common grounding in communication symbols {{cite:2a7d4a... | i | 491e072ebaa1a60457f5313ec95e09c3 |
System identification {{cite:aba5a0038025e71745026507231db9fba1cc5756}}, {{cite:f5fc2adc3f0e644efd42c8474d7ccde36899495c}} is a fundamental ingredient of many problems, such as model-predictive control {{cite:25b1fb85cca96472f57056f1c6802966e5b140e7}} and model-based reinforcement learning {{cite:5b33f493bf70c5ba638c80... | i | 818ea7d4f11cd2682581a19e3096ce4c |
This type of equations was initially considered by Ishii and Nakamura {{cite:34c56bc9d0742833da8fd9a34a5da5de0d454223}}, in which they investigated the existence, uniqueness and convergence of viscosity solutions. When it comes to regularity theory for Eq. (REF ), Di Castro, Kussi and Palatucci {{cite:1e5a1dff893a190a5... | i | e96fbd8eb2ab21d5f2035c307e6f0842 |
The Adam method is a sophisticated form of gradient descent. Recall that standard gradient descent involves computing {{formula:9585301e-e51a-4932-803f-5b42b4a2bf76}} , the partial derivatives with respect to each degree of freedom in {{formula:200e33f9-ed3a-4f6e-9bc9-f9faa64ca6e0}} (referred to as a free parameter), ... | m | 09c8409a05fa867503d89d764db5e550 |
As already mentioned, the computation of the stochastic reduced-order model (REF ) is costly. The cost of the reduced-order model in the moment-mean has complexity identical to classical deterministic model reduction methods and various state-of-the-art algorithms could be used to decrease the cost further. In fact, no... | d | ea0e661a27d5d535d6797044a09a901d |
In this Section, we present the experiments and the results of our study.
CIFAR-10 {{cite:db792ca4e28376c504e2cd31262891b7e2e2c07a}} is a popular dataset for image classification tasks.
It contains 50.000 train and 10.000 test data samples of tiny images (32px x 32px).
Each sample is assigned a label that belongs to on... | r | ef6ed93a4510ed6ef5bbbafb4bd534a3 |
Nešetřil and Ossona de Mendez {{cite:73d098bc58df8f85ba0a56189fb7e7af839bb5db}} give
examples that even if we replace “there exists a path of length {{formula:20b2dc00-85ac-44bc-aab4-172823109f92}}
between {{formula:3f96a993-1a85-4a0c-8511-10f3e04597f9}} and {{formula:719286da-6124-4d14-b477-9f0cd6779194}} ” by “ther... | r | 9b2edc70ca0cd1c5ae24c73c67fb7d45 |
Jagielski et al. {{cite:3b70402c00ed839caa52f06f68f2a905618a0e9a}} proposed a poisoning detection algorithm, TRIM, on linear regressions. TRIM recovers the legitimate non-poisoned dataset by searching for the keys that cause the largest loss and identify them as poisoning keys. There are two major limitations in applyi... | d | 1f115313eae2fc25999166e81d1b4c71 |
In recent times, large pre-trained neural network models have been successfully used to achieve state-of-the-art performance in computer vision (CV) {{cite:84fa5da71f662e94faa33d246512e25a0bf64a1e}}, {{cite:7abcb34f7fdced6e4cf8bc66a6f2c20da4189e58}}, {{cite:c5fcd28cb60a0770910f827e675a94755cd4b35e}}, {{cite:0559ce7a59b... | i | 0ff724f8fe12f587cd3308cc1086fab9 |
In this section, numerical simulations are provided for characterizing the proposed protocols. In our simulations, we consider a three-dimensional (3D) coordinate system where a uniform linear array (ULA) is used at the BS and a uniform rectangular array (URA) is employed at the RIS, which are located in the {{formula:... | r | ebe0035af70d54556b70b34981655e94 |
COCO human keypoint detection.
Our pre-trained model also works well when used downstream for human keypoint detection. In Table REF , we provide the results obtained when adapting our pre-trained model to a Keypoint R-CNN FPN {{cite:aa3cdbddf61660bfa92d303a96b397a32c0a5280}} model. Our approach achieves 65.7 AP{{formu... | r | cf9132f4b9a2578dc7ba43af967ef3df |
About two decades ago the first determinations of metallicity in high redshift star-forming galaxies {{cite:e4221d6ec0e60e9e1c22d0c7f4cef7bfc7841aae}}
and in damped Lyman-{{formula:b3bcb26d-72b6-46ad-95a7-cda82e58d31b}} systems {{cite:966ee1a498002052b8812713c315f38b0d970d01}} were obtained. From these results, among ... | d | 9dadacef24862bbcda2e753ce9fc5d15 |
We evaluate the performance of our mapping framework in the Carla simulation environment {{cite:f143ced046a4b0c45ea9dc6778d4748bfb36dd46}} and on a physical legged robot.
In simulation, we compare our method against two baselines representing state-of-the-art terrain property estimation methods and illustrate that our ... | r | 8504f16b169815d15479e193a032e0c2 |
EMA Confidence: As we can see in fig:fig3a, instantaneous confidence suffers from high variance across training epochs and is inaccurate for clean data detection. Incorrectly determined regularization power due to such instability leads to performance degradation. We use exponential moving average (EMA) along the epoc... | m | b91c609c19bb5ecb0ca11ecdea140d33 |
Any {{formula:9b7cf56e-b4ee-4906-8538-3f2ce9c7e531}} -dimensional algebra with non-trivial annihilator can be represented in
the form {{formula:a948de0f-bc0a-421c-9e71-ddce91cc9abf}} for some {{formula:bb34180e-6a36-4232-a64f-54f68a2544e0}} -dimensional algebra {{formula:c3c02d04-a4f3-4f3e-91df-f089675ae655}} , an {{f... | m | b0b67ef5da0f7f65ed313e284b3b0a85 |
We now seek to optimize the nonreciprocal response of the proposed elastic wave circulator by fixing the dimensionless modulation amplitude {{formula:2cceeee3-1d5e-41a9-9f3d-1877beebb9e3}} and sweeping over the drive and modulation frequencies. The objective function for the minimization problem is the ratio of the ab... | r | 5409253ea8829044a0afa20b57d49807 |
Nowadays, sequence transducer networks {{cite:04179dfe227b889ec5d71844636b6463bdbcdf4b}}, {{cite:66e74f5c73f3c42c00e29ac0b427f8c2e6e8ee6c}} are widely used for streaming automatic speech recognition due to their superior performance and compactness. A sequence transducer model has an encoder to capture the context info... | i | 0d6b1976f2a3f1d1b81b279d2267b901 |
(i){{formula:65028900-d7ab-474f-91b7-7788eb0f7427}} (ii). Suppose that {{formula:5ceb538e-9c88-4ff6-bbcf-b7494e7f7ed9}} is infinitely generated restricted-finite.
By Lemma REF (b), {{formula:397a0b9a-5826-4eee-8f5d-89f482b32092}} is locally finite. Hence by 14.3.7 of {{cite:8b286f4b41521767049a466c20d925829501456f}},... | r | 33af52eeeb5a4c3d0c6ff73aa7a2e0ec |
In order to achieve the optimal policy, policy gradient methods update parameters along the direction of estimated gradient. Vanilla Policy Gradient(PG) method REINFORCE and its variant GPOMDP using Natural Policy Gradient(NPG) methods were proposed and developed by {{cite:371cf220f639d6c50380b9c7b18e0caddfb39156}}, {{... | m | fbcd45b63799751854b3e06cb62dc5d9 |
Sensing viruses cause an immune defense system in host cells, and this induces acute IFN signaling activation followed by expression of IFNs. These IFNs amplify JAK/STAT signaling to promote the expression of various ISGs and accelerate subsequent cytokine signaling {{cite:e5f655df856142c757ccd5886b30bd721672dfcc}}. As... | d | ae7180118a736c72de6dd8326639d2a4 |
As a consequence of thm:CVRP, in cor:all we bound the approximation ratio of the iterated tour partitioning algorithm combined with the TSP algorithms for graphic metrics of Christofides {{cite:d96f5f5e09df88909f2fbe283bbf2c94b7ad3d71}}, of Mömke-Svensson {{cite:791ccd2d512c42e8794bc63bb98ce0520651ae3c}}, and of Sebő-V... | r | d558a31124780c67a84cfb0770e56599 |
In the paper {{cite:2ed6449679b339c086e2ecb7084ced5b2ac3b671}} the Bayesian approach to regularization is reviewed,
developing a function space viewpoint on the subject. A well-posedness theory
and some algorithmic approaches which are used when adopting the Bayesian
approach to inverse problems are introduced.
The fun... | d | a7db6ed645830ca4dd956070e347c06f |
In a word, the path integral approach provides a novel insight to study the evolutionary dynamics. We will consider the evolutionary process with eco-evolutionary feedback, environment fluctuation, the distinguishing selection intensity {{cite:8c72a0046bda599004e2bec67eb1c6ca40493a54}}, {{cite:74c6b544c1190ec06fe595ee1... | d | c4e0b0ac771d4926dae3591b3e117cde |
where {{formula:e0384cd1-161c-4e4c-bf2b-1279209c07f0}} is the output of the optimizer neural network {{formula:b55a4642-31f3-4ea5-9431-15f93da4a361}} with the parameters {{formula:6273a1ee-11ae-4dc1-9391-ec6ea1f7577a}} , inputs {{formula:95c48800-8487-4955-943e-3bd7fecfe97e}} and {{formula:7b885fe2-4f9d-4171-b6b9-af... | m | 67277a5e7f4fa1d9cacb97e836acc1c1 |
All setups (effectively non-regularized KRR (REF ), effectively regularized KRR (REF ) or optimally regularized KRR (REF ), (REF )) can therefore exhibit a crossover from an effectively noiseless regime (green or blue in Fig. REF ), to an effectively noisy regime (red, orange in Fig. REF ) depending on the quantity of ... | r | b024bc6bf405090cdd9c206b78ae7d52 |
There are several caveats in the present work. The spherical collapse is a simplistic model: the system does not take into account any effect of the environment or rotations and ignores mode-mode coupling. The first step forward is to consider triaxial collapse. Triaxial collapse, which is an important ingredient in mo... | d | fc86677cbe65149b0555c94c15f646a0 |
In light of recent revelations, we further evaluate our method on the new VQA debiasing dataset, GQA-OOD {{cite:fa8f25e482377285bb9cdb19635ec89cf7f03919}} and list our results in Table REF .
We compare our method to available recent state-of-the-art methods RUBi {{cite:33c93ebf80a302fbaa4fddaed7431664f9a8527d}}, LMH {{... | r | 2279c7a5325ed25da624afbaf9f6ae9d |
Assumptions REF , REF , REF are standard for analyzing {{formula:1945137a-533c-4aa8-91e8-dbb46fc9a177}} and identical to that of {{cite:d0063e9675000b6a365264eda3c26f145e31dc20}}. REF is convention for stochastic methods. Assumption REF mimics REF ; see rem:examples for discussions.
| m | 1b7c074bd912287b1dd3224731ecd4e9 |
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