Abstract is missing.
- A New Representation of Successor Features for Transfer across Dissimilar EnvironmentsMajid Abdolshah, Hung Le, Thommen George Karimpanal, Sunil Gupta 0001, Santu Rana, Svetha Venkatesh. 1-9 [doi]
- Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time ScalingKuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Rahimi Gorji, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Rohan Kumar Yadav. 10-20 [doi]
- Debiasing Model Updates for Improving Personalized Federated TrainingDurmus Alp Emre Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama. 21-31 [doi]
- Memory Efficient Online Meta LearningDurmus Alp Emre Acar, Ruizhao Zhu, Venkatesh Saligrama. 32-42 [doi]
- Robust Testing and Estimation under Manipulation AttacksJayadev Acharya, Ziteng Sun, Huanyu Zhang. 43-53 [doi]
- GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental LearningIdan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya. 54-65 [doi]
- f-Domain Adversarial Learning: Theory and AlgorithmsDavid Acuna, Guojun Zhang, Marc T. Law, Sanja Fidler. 66-75 [doi]
- Towards Rigorous Interpretations: a Formalisation of Feature AttributionDarius Afchar, Vincent Guigue, Romain Hennequin. 76-86 [doi]
- Acceleration via Fractal Learning Rate SchedulesNaman Agarwal, Surbhi Goel, Cyril Zhang. 87-99 [doi]
- A Regret Minimization Approach to Iterative Learning ControlNaman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh. 100-109 [doi]
- Towards the Unification and Robustness of Perturbation and Gradient Based ExplanationsSushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu 0001, Himabindu Lakkaraju. 110-119 [doi]
- Label Inference Attacks from Log-loss ScoresAbhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier. 120-129 [doi]
- Deep Kernel ProcessesLaurence Aitchison, Adam X. Yang, Sebastian W. Ober. 130-140 [doi]
- How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age EstimationAli Akbari, Muhammad Awais 0001, Manijeh Bashar, Josef Kittler. 141-151 [doi]
- On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student SettingShunta Akiyama, Taiji Suzuki. 152-162 [doi]
- Slot Machines: Discovering Winning Combinations of Random Weights in Neural NetworksMaxwell Mbabilla Aladago, Lorenzo Torresani. 163-174 [doi]
- A large-scale benchmark for few-shot program induction and synthesisFerran Alet, Javier Lopez-Contreras, James Koppel, Maxwell I. Nye, Armando Solar-Lezama, Tomás Lozano-Pérez, Leslie Pack Kaelbling, Joshua B. Tenenbaum. 175-186 [doi]
- Robust Pure Exploration in Linear Bandits with Limited BudgetAyya Alieva, Ashok Cutkosky, Abhimanyu Das. 187-195 [doi]
- Communication-Efficient Distributed Optimization with Quantized PreconditionersFoivos Alimisis, Peter Davies, Dan Alistarh. 196-206 [doi]
- Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss FunctionsPierre Alquier. 207-218 [doi]
- Dataset Dynamics via Gradient Flows in Probability SpaceDavid Alvarez-Melis, Nicolò Fusi. 219-230 [doi]
- Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive ComplexityGeorgios Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti-Spaccamela, Rebecca Reiffenhäuser. 231-242 [doi]
- Safe Reinforcement Learning with Linear Function ApproximationSanae Amani, Christos Thrampoulidis, Lin Yang 0011. 243-253 [doi]
- Automatic variational inference with cascading flowsLuca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven. 254-263 [doi]
- Sparse Bayesian Learning via Stepwise RegressionSebastian E. Ament, Carla P. Gomes. 264-274 [doi]
- Locally Persistent Exploration in Continuous Control Tasks with Sparse RewardsSusan Amin, Maziar Gomrokchi, Hossein Aboutalebi, Harsh Satija, Doina Precup. 275-285 [doi]
- Preferential Temporal Difference LearningNishanth V. Anand, Doina Precup. 286-296 [doi]
- Unitary Branching Programs: Learnability and Lower BoundsFidel Ernesto Diaz Andino, Maria Kokkou, Mateus de Oliveira Oliveira, Farhad Vadiee. 297-306 [doi]
- The Logical Options FrameworkBrandon Araki, Xiao Li 0025, Kiran Vodrahalli, Jonathan A. DeCastro, Micah J. Fry, Daniela Rus. 307-317 [doi]
- Annealed Flow Transport Monte CarloMichael Arbel, Alexander G. de G. Matthews, Arnaud Doucet. 318-330 [doi]
- Permutation WeightingDavid Arbour, Drew Dimmery, Arjun Sondhi. 331-341 [doi]
- Analyzing the tree-layer structure of Deep ForestsLudovic Arnould, Claire Boyer, Erwan Scornet. 342-350 [doi]
- Dropout: Explicit Forms and Capacity ControlRaman Arora, Peter Bartlett, Poorya Mianjy, Nathan Srebro. 351-361 [doi]
- Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate GradientsArtem Artemev, David R. Burt, Mark van der Wilk. 362-372 [doi]
- Deciding What to Learn: A Rate-Distortion ApproachDilip Arumugam, Benjamin Van Roy. 373-382 [doi]
- Private Adaptive Gradient Methods for Convex OptimizationHilal Asi, John C. Duchi, Alireza Fallah 0001, Omid Javidbakht, Kunal Talwar. 383-392 [doi]
- Private Stochastic Convex Optimization: Optimal Rates in L1 GeometryHilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar. 393-403 [doi]
- Combinatorial Blocking Bandits with Stochastic DelaysAlexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu 0001, Constantine Caramanis, Sanjay Shakkottai. 404-413 [doi]
- Dichotomous Optimistic Search to Quantify Human PerceptionJulien Audiffren. 414-424 [doi]
- Federated Learning under Arbitrary Communication PatternsDmitrii Avdiukhin, Shiva Prasad Kasiviswanathan. 425-435 [doi]
- Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior KnowledgeRotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Yehuda Levy. 436-445 [doi]
- Decomposable Submodular Function Minimization via Maximum FlowKyriakos Axiotis, Adam Karczmarz, Anish Mukherjee 0001, Piotr Sankowski, Adrian Vladu. 446-456 [doi]
- Differentially Private Query Release Through Adaptive ProjectionSergül Aydöre, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth 0001, Ankit A. Siva. 457-467 [doi]
- On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror DescentShahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake E. Woodworth, Nathan Srebro, Amir Globerson, Daniel Soudry. 468-477 [doi]
- On-Off Center-Surround Receptive Fields for Accurate and Robust Image ClassificationZahra Babaiee, Ramin M. Hasani, Mathias Lechner, Daniela Rus, Radu Grosu. 478-489 [doi]
- Uniform Convergence, Adversarial Spheres and a Simple RemedyGregor Bachmann, Seyed-Mohsen Moosavi-Dezfooli, Thomas Hofmann. 490-499 [doi]
- Faster Kernel Matrix Algebra via Density EstimationArturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner. 500-510 [doi]
- Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance GuaranteesKishan Panaganti Badrinath, Dileep Kalathil. 511-520 [doi]
- Skill Discovery for Exploration and Planning using Deep Skill GraphsAkhil Bagaria, Jason K. Senthil, George Konidaris 0001. 521-531 [doi]
- Locally Adaptive Label Smoothing Improves Predictive ChurnDara Bahri, Heinrich Jiang. 532-542 [doi]
- How Important is the Train-Validation Split in Meta-Learning?Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham M. Kakade, Huan Wang, Caiming Xiong. 543-553 [doi]
- Stabilizing Equilibrium Models by Jacobian RegularizationShaojie Bai, Vladlen Koltun, J. Zico Kolter. 554-565 [doi]
- Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary ClassificationYu Bai, Song Mei, Huan Wang, Caiming Xiong. 566-576 [doi]
- Principled Exploration via Optimistic Bootstrapping and Backward InductionChenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu 0008, Zhaoran Wang. 577-587 [doi]
- GLSearch: Maximum Common Subgraph Detection via Learning to SearchYunsheng Bai, Derek Xu, Yizhou Sun, Wei Wang 0010. 588-598 [doi]
- Breaking the Limits of Message Passing Graph Neural NetworksMuhammet Balcilar, Pierre Héroux, Benoit Gaüzère, Pascal Vasseur, Sébastien Adam, Paul Honeine. 599-608 [doi]
- Instance Specific Approximations for Submodular MaximizationEric Balkanski, Sharon Qian, Yaron Singer. 609-618 [doi]
- Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline EnvironmentPhilip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts. 619-629 [doi]
- Regularized Online Allocation Problems: Fairness and BeyondSantiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni. 630-639 [doi]
- Predict then Interpolate: A Simple Algorithm to Learn Stable ClassifiersYujia Bao, Shiyu Chang, Regina Barzilay. 640-650 [doi]
- Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable ModelsFan Bao, Kun Xu 0004, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang 0010. 651-661 [doi]
- Compositional Video Synthesis with Action GraphsAmir Bar, Roei Herzig, Xiaolong Wang 0004, Anna Rohrbach, Gal Chechik, Trevor Darrell, Amir Globerson. 662-673 [doi]
- Approximating a Distribution Using Weight QueriesNadav Barak, Sivan Sabato. 674-683 [doi]
- Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution GeneralizationAseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath. 684-693 [doi]
- Training Quantized Neural Networks to Global Optimality via Semidefinite ProgrammingBurak Bartan, Mert Pilanci. 694-704 [doi]
- 2(T) regret for decentralized bandits in matching marketsSoumya Basu 0001, Karthik Abinav Sankararaman, Abishek Sankararaman. 705-715 [doi]
- Optimal Thompson Sampling strategies for support-aware CVaR banditsDorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric Maillard. 716-726 [doi]
- On Limited-Memory Subsampling Strategies for BanditsDorian Baudry, Yoan Russac, Olivier Cappé. 727-737 [doi]
- Generalized Doubly Reparameterized Gradient EstimatorsMatthias Bauer, Andriy Mnih. 738-747 [doi]
- Directional Graph NetworksDominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Lió. 748-758 [doi]
- Policy Analysis using Synthetic Controls in Continuous-TimeAlexis Bellot, Mihaela van der Schaar. 759-768 [doi]
- Loss Surface Simplexes for Mode Connecting Volumes and Fast EnsemblingGregory W. Benton, Wesley Maddox, Sanae Lotfi, Andrew Gordon Wilson. 769-779 [doi]
- TFix: Learning to Fix Coding Errors with a Text-to-Text TransformerBerkay Berabi, Jingxuan He, Veselin Raychev, Martin T. Vechev. 780-791 [doi]
- Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival AnalysisJeroen Berrevoets, Ahmed M. Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela van der Schaar. 792-802 [doi]
- Learning from Biased Data: A Semi-Parametric ApproachPatrice Bertail, Stéphan Clémençon, Yannick Guyonvarch, Nathan Noiry. 803-812 [doi]
- Is Space-Time Attention All You Need for Video Understanding?Gedas Bertasius, Heng Wang, Lorenzo Torresani. 813-824 [doi]
- Confidence Scores Make Instance-dependent Label-noise Learning PossibleAntonin Berthon, Bo Han 0003, Gang Niu 0001, Tongliang Liu, Masashi Sugiyama. 825-836 [doi]
- Size-Invariant Graph Representations for Graph Classification ExtrapolationsBeatrice Bevilacqua, Yangze Zhou, Bruno Ribeiro 0001. 837-851 [doi]
- Principal Bit Analysis: Autoencoding with Schur-Concave LossSourbh Bhadane, Aaron B. Wagner, Jayadev Acharya. 852-862 [doi]
- Lower Bounds on Cross-Entropy Loss in the Presence of Test-time AdversariesArjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal. 863-873 [doi]
- Additive Error Guarantees for Weighted Low Rank ApproximationAditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena. 874-883 [doi]
- Sample Complexity of Robust Linear Classification on Separated DataRobi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri. 884-893 [doi]
- Finding k in Latent k- polytopeChiranjib Bhattacharyya, Ravindran Kannan, Amit Kumar 0001. 894-903 [doi]
- Non-Autoregressive Electron Redistribution Modeling for Reaction PredictionHangrui Bi, Hengyi Wang, Chence Shi, Connor W. Coley, Jian Tang 0005, Hongyu Guo. 904-913 [doi]
- TempoRL: Learning When to ActAndré Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer. 914-924 [doi]
- Follow-the-Regularized-Leader Routes to Chaos in Routing GamesJakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski, Grzegorz Kosiorowski, Michal Misiurewicz, Georgios Piliouras. 925-935 [doi]
- Neural Symbolic Regression that scalesLuca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurélien Lucchi, Giambattista Parascandolo. 936-945 [doi]
- Model Distillation for Revenue Optimization: Interpretable Personalized PricingMax Biggs, Wei Sun 0031, Markus Ettl. 946-956 [doi]
- Scalable Normalizing Flows for Permutation Invariant DensitiesMarin Bilos, Stephan Günnemann. 957-967 [doi]
- Online Learning for Load Balancing of Unknown Monotone Resource Allocation GamesIlai Bistritz, Nicholas Bambos. 968-979 [doi]
- Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half PrecisionJohan Björck, Xiangyu Chen, Christopher De Sa, Carla P. Gomes, Kilian Q. Weinberger. 980-991 [doi]
- Multiplying Matrices Without MultiplyingDavis W. Blalock, John V. Guttag. 992-1004 [doi]
- One for One, or All for All: Equilibria and Optimality of Collaboration in Federated LearningAvrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao. 1005-1014 [doi]
- Black-box density function estimation using recursive partitioningErik Bodin, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek. 1015-1025 [doi]
- Weisfeiler and Lehman Go Topological: Message Passing Simplicial NetworksCristian Bodnar, Fabrizio Frasca, Yuguang Wang 0001, Nina Otter, Guido F. Montúfar, Pietro Lió, Michael M. Bronstein. 1026-1037 [doi]
- The Hintons in your Neural Network: a Quantum Field Theory View of Deep LearningRoberto Bondesan, Max Welling. 1038-1048 [doi]
- Offline Contextual Bandits with Overparameterized ModelsDavid Brandfonbrener, William F. Whitney, Rajesh Ranganath, Joan Bruna. 1049-1058 [doi]
- High-Performance Large-Scale Image Recognition Without NormalizationAndy Brock, Soham De, Samuel L. Smith, Karen Simonyan. 1059-1071 [doi]
- Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte CarloJames A. Brofos, Roy R. Lederman. 1072-1081 [doi]
- Reinforcement Learning of Implicit and Explicit Control Flow InstructionsEthan A. Brooks, Janarthanan Rajendran, Richard L. Lewis, Satinder Singh. 1082-1091 [doi]
- Machine Unlearning for Random ForestsJonathan Brophy, Daniel Lowd. 1092-1104 [doi]
- Value Alignment VerificationDaniel S. Brown, Jordan Schneider, Anca D. Dragan, Scott Niekum. 1105-1115 [doi]
- Model-Free and Model-Based Policy Evaluation when Causality is UncertainDavid Bruns-Smith. 1116-1126 [doi]
- Narrow Margins: Classification, Margins and Fat TailsFrancois Buet-Golfouse. 1127-1135 [doi]
- Differentially Private Correlation ClusteringMark Bun, Marek Eliás 0001, Janardhan Kulkarni. 1136-1146 [doi]
- Disambiguation of Weak Supervision leading to Exponential Convergence ratesVivien A. Cabannnes, Francis R. Bach, Alessandro Rudi. 1147-1157 [doi]
- Finite mixture models do not reliably learn the number of componentsDiana Cai, Trevor Campbell, Tamara Broderick. 1158-1169 [doi]
- A Theory of Label Propagation for Subpopulation ShiftTianle Cai, RuiQi Gao, Jason Lee, Qi Lei. 1170-1182 [doi]
- Lenient Regret and Good-Action Identification in Gaussian Process BanditsXu Cai, Selwyn Gomes, Jonathan Scarlett. 1183-1192 [doi]
- A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box OptimizationHanQin Cai, Yuchen Lou, Daniel McKenzie, Wotao Yin. 1193-1203 [doi]
- GraphNorm: A Principled Approach to Accelerating Graph Neural Network TrainingTianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang 0001. 1204-1215 [doi]
- On Lower Bounds for Standard and Robust Gaussian Process Bandit OptimizationXu Cai, Jonathan Scarlett. 1216-1226 [doi]
- High-dimensional Experimental Design and Kernel BanditsRomain Camilleri, Kevin Jamieson, Julian Katz-Samuels. 1227-1237 [doi]
- A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter OptimizationAndrew Campbell, Wenlong Chen, Vincent Stimper, José Miguel Hernández-Lobato, Yichuan Zhang. 1238-1248 [doi]
- Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise InjectionsAlexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli. 1249-1260 [doi]
- Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein DesignYue Cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen. 1261-1271 [doi]
- Learning from Similarity-Confidence DataYuzhou Cao, Lei Feng, Yitian Xu, Bo An 0001, Gang Niu 0001, Masashi Sugiyama. 1272-1282 [doi]
- Parameter-free Locally Accelerated Conditional GradientsAlejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta. 1283-1293 [doi]
- Optimizing persistent homology based functionsMathieu Carrière, Frédéric Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda. 1294-1303 [doi]
- Online Policy Gradient for Model Free Learning of Linear Quadratic Regulators with √T RegretAsaf Cassel, Tomer Koren. 1304-1313 [doi]
- Multi-Receiver Online Bayesian PersuasionMatteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti 0001. 1314-1323 [doi]
- Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining DataAmnon Catav, Boyang Fu, Yazeed Zoabi, Ahuva Weiss-Meilik, Noam Shomron, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach. 1324-1335 [doi]
- Disentangling syntax and semantics in the brain with deep networksCharlotte Caucheteux, Alexandre Gramfort, Jean-Remi King. 1336-1348 [doi]
- Fair Classification with Noisy Protected Attributes: A Framework with Provable GuaranteesL. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi. 1349-1361 [doi]
- Best Model Identification: A Rested Bandit FormulationLeonardo Cella, Massimiliano Pontil, Claudio Gentile. 1362-1372 [doi]
- Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning researchJohan Samir Obando-Ceron, Pablo Samuel Castro. 1373-1383 [doi]
- Learning Routines for Effective Off-Policy Reinforcement LearningEdoardo Cetin, Oya Çeliktutan. 1384-1394 [doi]
- Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction NetworksCiwan Ceylan, Salla Franzén, Florian T. Pokorny. 1395-1406 [doi]
- GRAND: Graph Neural DiffusionBen Chamberlain 0001, James Rowbottom, Maria Gorinova, Michael M. Bronstein, Stefan Webb, Emanuele Rossi. 1407-1418 [doi]
- HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical ProjectionsInes Chami, Albert Gu, Dat Nguyen, Christopher Ré. 1419-1429 [doi]
- Goal-Conditioned Reinforcement Learning with Imagined SubgoalsElliot Chane-Sane, Cordelia Schmid, Ivan Laptev. 1430-1440 [doi]
- Locally Private k-Means in One RoundAlisa Chang, Badih Ghazi, Ravi Kumar 0001, Pasin Manurangsi. 1441-1451 [doi]
- Modularity in Reinforcement Learning via Algorithmic Independence in Credit AssignmentMichael Chang 0003, Sidhant Kaushik, Sergey Levine, Tom Griffiths. 1452-1462 [doi]
- Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed DetectionNadine Chang, Zhiding Yu, Yu-Xiong Wang, Animashree Anandkumar, Sanja Fidler, Jose M. Alvarez. 1463-1472 [doi]
- DeepWalking Backwards: From Embeddings Back to GraphsSudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis. 1473-1483 [doi]
- Differentiable Spatial Planning using TransformersDevendra Singh Chaplot, Deepak Pathak, Jitendra Malik. 1484-1495 [doi]
- Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement LearningHenry Charlesworth, Giovanni Montana. 1496-1506 [doi]
- Classification with Rejection Based on Cost-sensitive ClassificationNontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama. 1507-1517 [doi]
- Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic SkillsYevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine. 1518-1528 [doi]
- Unified Robust Semi-Supervised Variational AutoencoderXu Chen. 1529-1538 [doi]
- Unsupervised Learning of Visual 3D Keypoints for ControlBoyuan Chen, Pieter Abbeel, Deepak Pathak. 1539-1549 [doi]
- Integer Programming for Causal Structure Learning in the Presence of Latent VariablesRui Chen, Sanjeeb Dash, Tian Gao. 1550-1560 [doi]
- Improved Corruption Robust Algorithms for Episodic Reinforcement LearningYifang Chen, Simon S. Du, Kevin Jamieson. 1561-1570 [doi]
- Scalable Computations of Wasserstein Barycenter via Input Convex Neural NetworksYongxin Chen, JiaoJiao Fan, Amirhossein Taghvaei. 1571-1581 [doi]
- Neural Feature Matching in Implicit 3D RepresentationsYunlu Chen, Basura Fernando, Hakan Bilen, Thomas Mensink, Efstratios Gavves. 1582-1593 [doi]
- Decentralized Riemannian Gradient Descent on the Stiefel ManifoldShixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour. 1594-1605 [doi]
- Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential RecommendationChao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang. 1606-1616 [doi]
- Mandoline: Model Evaluation under Distribution ShiftMayee F. Chen, Karan Goel, Nimit Sharad Sohoni, Fait Poms, Kayvon Fatahalian, Christopher Ré. 1617-1629 [doi]
- Order Matters: Probabilistic Modeling of Node Sequence for Graph GenerationXiaohui Chen, Xu Han, Jiajing Hu, Francisco J. R. Ruiz, Li-Ping Liu. 1630-1639 [doi]
- CARTL: Cooperative Adversarially-Robust Transfer LearningDian Chen 0004, Hongxin Hu, Qian Wang 0002, Yinli Li, Cong Wang 0001, Chao Shen, Qi Li 0002. 1640-1650 [doi]
- Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition CaseLiyu Chen, Haipeng Luo. 1651-1660 [doi]
- SpreadsheetCoder: Formula Prediction from Semi-structured ContextXinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou. 1661-1672 [doi]
- Large-Margin Contrastive Learning with Distance Polarization RegularizerShuo Chen 0003, Gang Niu 0001, Chen Gong 0002, Jun Li, Jian Yang, Masashi Sugiyama. 1673-1683 [doi]
- Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series ForecastingYuzhou Chen, Ignacio Segovia-Dominguez, Yulia R. Gel. 1684-1694 [doi]
- A Unified Lottery Ticket Hypothesis for Graph Neural NetworksTianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang. 1695-1706 [doi]
- Network Inference and Influence Maximization from SamplesWei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang. 1707-1716 [doi]
- Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic MapsRenyi Chen, Molei Tao. 1717-1727 [doi]
- Analysis of stochastic Lanczos quadrature for spectrum approximationTyler Chen, Thomas Trogdon, Shashanka Ubaru. 1728-1739 [doi]
- Large-Scale Multi-Agent Deep FBSDEsTianrong Chen, Ziyi Wang, Ioannis Exarchos, Evangelos A. Theodorou. 1740-1748 [doi]
- Representation Subspace Distance for Domain Adaptation RegressionXinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long. 1749-1759 [doi]
- Overcoming Catastrophic Forgetting by Bayesian Generative RegularizationPei-Hung Chen, Wei Wei 0025, Cho-Jui Hsieh, Bo Dai. 1760-1770 [doi]
- Cyclically Equivariant Neural Decoders for Cyclic CodesXiangyu Chen, Min Ye. 1771-1780 [doi]
- A Receptor Skeleton for Capsule Neural NetworksJintai Chen, Hongyun Yu, Chengde Qian, Danny Z. Chen, Jian Wu 0001. 1781-1790 [doi]
- Accelerating Gossip SGD with Periodic Global AveragingYiming Chen 0003, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin. 1791-1802 [doi]
- ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed TrainingJianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael W. Mahoney, Joseph Gonzalez 0001. 1803-1813 [doi]
- SPADE: A Spectral Method for Black-Box Adversarial Robustness EvaluationWuxinlin Cheng, Chenhui Deng, Zhiqiang Zhao, Yaohui Cai, Zhiru Zhang, Zhuo Feng. 1814-1824 [doi]
- Self-supervised and Supervised Joint Training for Resource-rich Machine TranslationYong Cheng, Wei Wang, Lu Jiang, Wolfgang Macherey. 1825-1835 [doi]
- Exact Optimization of Conformal Predictors via Incremental and Decremental LearningGiovanni Cherubin, Konstantinos Chatzikokolakis 0001, Martin Jaggi. 1836-1845 [doi]
- Problem Dependent View on Structured Thresholding Bandit ProblemsJames Cheshire, Pierre Ménard, Alexandra Carpentier. 1846-1854 [doi]
- Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré RecurrenceYun Kuen Cheung, Georgios Piliouras. 1855-1865 [doi]
- Understanding and Mitigating Accuracy Disparity in RegressionJianfeng Chi, Yuan Tian 0001, Geoffrey J. Gordon, Han Zhao 0002. 1866-1876 [doi]
- Private Alternating Least Squares: Practical Private Matrix Completion with Tighter RatesSteve Chien, Prateek Jain 0002, Walid Krichene, Steffen Rendle, Shuang Song 0001, Abhradeep Thakurta, Li Zhang 0069. 1877-1887 [doi]
- Light RUMsFlavio Chierichetti, Ravi Kumar 0001, Andrew Tomkins. 1888-1897 [doi]
- Parallelizing Legendre Memory Unit TrainingNarsimha Reddy Chilkuri, Chris Eliasmith. 1898-1907 [doi]
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- Active Slices for Sliced Stein DiscrepancyWenbo Gong 0001, Kaibo Zhang, Yingzhen Li, José Miguel Hernández-Lobato. 3766-3776 [doi]
- On the Problem of Underranking in Group-Fair RankingSruthi Gorantla, Amit Deshpande, Anand Louis. 3777-3787 [doi]
- MARINA: Faster Non-Convex Distributed Learning with CompressionEduard A. Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtárik. 3788-3798 [doi]
- Systematic Analysis of Cluster Similarity Indices: How to Validate Validation MeasuresMartijn Gösgens, Alexey Tikhonov, Liudmila Prokhorenkova. 3799-3808 [doi]
- Revisiting Point Cloud Shape Classification with a Simple and Effective BaselineAnkit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng 0001. 3809-3820 [doi]
- Dissecting Supervised Constrastive LearningFlorian Graf, Christoph D. Hofer, Marc Niethammer, Roland Kwitt. 3821-3830 [doi]
- Oops I Took A Gradient: Scalable Sampling for Discrete DistributionsWill Grathwohl, Kevin Swersky, Milad Hashemi, David Duvenaud, Chris J. Maddison. 3831-3841 [doi]
- Detecting Rewards Deterioration in Episodic Reinforcement LearningIdo Greenberg, Shie Mannor. 3842-3853 [doi]
- Crystallization Learning with the Delaunay TriangulationJiaqi Gu, Guosheng Yin. 3854-3863 [doi]
- AutoAttend: Automated Attention Representation SearchChaoyu Guan, Xin Wang, Wenwu Zhu 0001. 3864-3874 [doi]
- Operationalizing Complex Causes: A Pragmatic View of MediationLimor Gultchin, David S. Watson, Matt J. Kusner, Ricardo Silva. 3875-3885 [doi]
- On a Combination of Alternating Minimization and Nesterov's MomentumSergey Guminov, Pavel E. Dvurechensky, Nazarii Tupitsa, Alexander V. Gasnikov. 3886-3898 [doi]
- Decentralized Single-Timescale Actor-Critic on Zero-Sum Two-Player Stochastic GamesHongyi Guo, Zuyue Fu, Zhuoran Yang, Zhaoran Wang. 3899-3909 [doi]
- Adversarial Policy Learning in Two-player Competitive GamesWenbo Guo 0002, Xian Wu, Sui Huang, Xinyu Xing. 3910-3919 [doi]
- Soft then Hard: Rethinking the Quantization in Neural Image CompressionZongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen 0001. 3920-3929 [doi]
- UneVEn: Universal Value Exploration for Multi-Agent Reinforcement LearningTarun Gupta 0002, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson. 3930-3941 [doi]
- Distribution-Free Calibration Guarantees for Histogram Binning without Sample SplittingChirag Gupta, Aaditya Ramdas. 3942-3952 [doi]
- Correcting Exposure Bias for Link RecommendationShantanu Gupta, Hao Wang, Zachary Lipton, Yuyang Wang. 3953-3963 [doi]
- The Heavy-Tail Phenomenon in SGDMert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu. 3964-3975 [doi]
- Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial AttacksNezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang 0001, Bo Li. 3976-3987 [doi]
- Adapting to Delays and Data in Adversarial Multi-Armed BanditsAndrás György 0001, Pooria Joulani. 3988-3997 [doi]
- Rate-Distortion Analysis of Minimum Excess Risk in Bayesian LearningHassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei, Mahdieh Soleymani Baghshah. 3998-4007 [doi]
- Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient ApproachNadav Hallak, Panayotis Mertikopoulos, Volkan Cevher. 4008-4017 [doi]
- Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient ExplorationSeungyul Han, Youngchul Sung. 4018-4029 [doi]
- Adversarial Combinatorial Bandits with General Non-linear Reward FunctionsYanjun Han, Yining Wang, Xi Chen. 4030-4039 [doi]
- A Collective Learning Framework to Boost GNN Expressiveness for Node ClassificationMengyue Hang, Jennifer Neville, Bruno Ribeiro 0001. 4040-4050 [doi]
- Grounding Language to Entities and Dynamics for Generalization in Reinforcement LearningAustin W. Hanjie, Victor Zhong, Karthik Narasimhan. 4051-4062 [doi]
- Sparse Feature Selection Makes Batch Reinforcement Learning More Sample EfficientBotao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang. 4063-4073 [doi]
- Bootstrapping Fitted Q-Evaluation for Off-Policy InferenceBotao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang. 4074-4084 [doi]
- Compressed Maximum LikelihoodYi Hao, Alon Orlitsky. 4085-4095 [doi]
- Valid Causal Inference with (Some) Invalid InstrumentsJason S. Hartford, Victor Veitch, Dhanya Sridhar, Kevin Leyton-Brown. 4096-4106 [doi]
- Model Performance Scaling with Multiple Data SourcesTatsunori Hashimoto. 4107-4116 [doi]
- Hierarchical VAEs Know What They Don't KnowJakob Drachmann Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe. 4117-4128 [doi]
- Defense against backdoor attacks via robust covariance estimationJonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh. 4129-4139 [doi]
- Boosting for Online Convex OptimizationElad Hazan, Karan Singh. 4140-4149 [doi]
- PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale ModelsChaoyang He 0001, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr. 4150-4159 [doi]
- SoundDet: Polyphonic Moving Sound Event Detection and Localization from Raw WaveformYuhang He, Niki Trigoni, Andrew Markham. 4160-4170 [doi]
- Logarithmic Regret for Reinforcement Learning with Linear Function ApproximationJiafan He, Dongruo Zhou, Quanquan Gu. 4171-4180 [doi]
- Finding Relevant Information via a Discrete Fourier ExpansionMohsen Heidari, Jithin K. Sreedharan, Gil I. Shamir, Wojciech Szpankowski. 4181-4191 [doi]
- Zeroth-Order Non-Convex Learning via Hierarchical Dual AveragingAmélie Héliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier. 4192-4202 [doi]
- Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced SparsityRyan Henderson, Djork-Arné Clevert, Floriane Montanari. 4203-4213 [doi]
- Muesli: Combining Improvements in Policy OptimizationMatteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theophane Weber, David Silver, Hado van Hasselt. 4214-4226 [doi]
- Learning Representations by Humans, for HumansSophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes. 4227-4238 [doi]
- Optimizing Black-box Metrics with Iterative Example WeightingGaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo. 4239-4249 [doi]
- Trees with Attention for Set Prediction TasksRoy Hirsch, Ran Gilad-Bachrach. 4250-4261 [doi]
- Multiplicative Noise and Heavy Tails in Stochastic OptimizationLiam Hodgkinson, Michael W. Mahoney. 4262-4274 [doi]
- MC-LSTM: Mass-Conserving LSTMPieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer. 4275-4286 [doi]
- Learning Curves for Analysis of Deep NetworksDerek Hoiem, Tanmay Gupta, Zhizhong Li 0001, Michal Shlapentokh-Rothman. 4287-4296 [doi]
- Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural ProcessesPeter Holderrieth, Michael Hutchinson, Yee Whye Teh. 4297-4307 [doi]
- Latent Programmer: Discrete Latent Codes for Program SynthesisJoey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer. 4308-4318 [doi]
- Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix MultiplicationSangwoo Hong, Heecheol Yang, YoungSeok Yoon, Taehyun Cho, Jungwoo Lee 0001. 4319-4327 [doi]
- Federated Learning of User Verification Models Without Sharing EmbeddingsHossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph Soriaga, Max Welling. 4328-4336 [doi]
- The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical SetsYa-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher. 4337-4348 [doi]
- Near-Optimal Representation Learning for Linear Bandits and Linear RLJiachen Hu, Xiaoyu Chen, Chi Jin, Lihong Li, Liwei Wang 0001. 4349-4358 [doi]
- On the Random Conjugate Kernel and Neural Tangent KernelZhengmian Hu, Heng Huang. 4359-4368 [doi]
- Off-Belief LearningHengyuan Hu, Adam Lerer, Brandon Cui, Luis-Pineda, Noam Brown, Jakob N. Foerster. 4369-4379 [doi]
- Generalizable Episodic Memory for Deep Reinforcement LearningHao Hu, Jianing Ye, Guangxiang Zhu, Zhizhou Ren, Chongjie Zhang. 4380-4390 [doi]
- A Scalable Deterministic Global Optimization Algorithm for Clustering ProblemsKaixun Hua, Mingfei Shi, Yankai Cao. 4391-4401 [doi]
- On Recovering from Modeling Errors Using Testing Bayesian NetworksHaiying Huang, Adnan Darwiche. 4402-4411 [doi]
- A Novel Sequential Coreset Method for Gradient Descent AlgorithmsJiawei Huang, Ruomin Huang, Wenjie Liu, Nikolaos M. Freris, Hu Ding. 4412-4422 [doi]
- FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning AnalysisBaihe Huang, Xiaoxiao Li, Zhao Song 0002, Xin Yang 0017. 4423-4434 [doi]
- STRODE: Stochastic Boundary Ordinary Differential EquationHengguan Huang, Hongfu Liu, Hao Wang 0014, Chang Xiao, Ye Wang. 4435-4445 [doi]
- A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein DistanceMinhui Huang, Shiqian Ma, Lifeng Lai. 4446-4455 [doi]
- Projection Robust Wasserstein BarycentersMinhui Huang, Shiqian Ma, Lifeng Lai. 4456-4465 [doi]
- Accurate Post Training Quantization With Small Calibration SetsItay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry. 4466-4475 [doi]
- Learning and Planning in Complex Action SpacesThomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Mohammadamin Barekatain, Simon Schmitt, David Silver. 4476-4486 [doi]
- Generative Adversarial TransformersDrew A. Hudson, Larry Zitnick. 4487-4499 [doi]
- Neural Pharmacodynamic State Space ModelingZeshan Hussain, Rahul G. Krishnan, David Sontag. 4500-4510 [doi]
- Hyperparameter Selection for Imitation LearningLéonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphaël Marinier, Lukasz Stafiniak, Manu Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin. 4511-4522 [doi]
- Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed DistributionsTodd Huster, Jeremy E. J. Cohen, Zinan Lin 0001, Kevin Chan, Charles A. Kamhoua, Nandi O. Leslie, Cho-Yu Jason Chiang, Vyas Sekar. 4523-4532 [doi]
- LieTransformer: Equivariant Self-Attention for Lie GroupsMichael Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim. 4533-4543 [doi]
- Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix FactorizationShahana Ibrahim, Xiao Fu 0001. 4544-4554 [doi]
- Selecting Data Augmentation for Simulating InterventionsMaximilian Ilse, Jakub M. Tomczak, Patrick Forré. 4555-4562 [doi]
- Scalable Marginal Likelihood Estimation for Model Selection in Deep LearningAlexander Immer, Matthias Bauer, Vincent Fortuin, Gunnar Rätsch, Mohammad Emtiyaz Khan. 4563-4573 [doi]
- Active Learning for Distributionally Robust Level-Set EstimationYu Inatsu, Shogo Iwazaki, Ichiro Takeuchi. 4574-4584 [doi]
- Learning Randomly Perturbed Structured Predictors for Direct Loss MinimizationHedda Cohen Indelman, Tamir Hazan. 4585-4595 [doi]
- Randomized Entity-wise Factorization for Multi-Agent Reinforcement LearningShariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha. 4596-4606 [doi]
- Randomized Exploration in Reinforcement Learning with General Value Function ApproximationHaque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin Yang. 4607-4616 [doi]
- Distributed Second Order Methods with Fast Rates and Compressed CommunicationRustem Islamov, Xun Qian, Peter Richtárik. 4617-4628 [doi]
- What Are Bayesian Neural Network Posteriors Really Like?Pavel Izmailov, Sharad Vikram, Matthew D. Hoffman, Andrew Gordon Wilson. 4629-4640 [doi]
- How to Learn when Data Reacts to Your Model: Performative Gradient DescentZachary Izzo, Lexing Ying, James Zou 0001. 4641-4650 [doi]
- Perceiver: General Perception with Iterative AttentionAndrew Jaegle, Felix Gimeno, Andy Brock, Oriol Vinyals, Andrew Zisserman, João Carreira. 4651-4664 [doi]
- Imitation by Predicting ObservationsAndrew Jaegle, Yury Sulsky, Arun Ahuja, Jake Bruce, Rob Fergus, Greg Wayne. 4665-4676 [doi]
- Local Correlation Clustering with Asymmetric Classification ErrorsJafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev. 4677-4686 [doi]
- Alternative Microfoundations for Strategic ClassificationMeena Jagadeesan, Celestine Mendler-Dünner, Moritz Hardt. 4687-4697 [doi]
- Robust Density Estimation from Batches: The Best Things in Life are (Nearly) FreeAyush Jain, Alon Orlitsky. 4698-4708 [doi]
- Instance-Optimal Compressed Sensing via Posterior SamplingAjil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price. 4709-4720 [doi]
- Fairness for Image Generation with Uncertain Sensitive AttributesAjil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price. 4721-4732 [doi]
- Feature Clustering for Support Identification in Extreme RegionsHamid Jalalzai, Rémi Leluc. 4733-4743 [doi]
- Improved Regret Bounds of Bilinear Bandits using Action Space AnalysisKyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang. 4744-4754 [doi]
- Inverse Decision Modeling: Learning Interpretable Representations of BehaviorDaniel Jarrett, Alihan Hüyük, Mihaela van der Schaar. 4755-4771 [doi]
- Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts GeneralizationStanislaw Jastrzebski, Devansh Arpit, Oliver Åstrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, KyungHyun Cho, Krzysztof J. Geras. 4772-4784 [doi]
- Policy Gradient Bayesian Robust Optimization for Imitation LearningZaynah Javed, Daniel S. Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca D. Dragan, Ken Goldberg. 4785-4796 [doi]
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- Parallel and Flexible Sampling from Autoregressive Models via Langevin DynamicsVivek Jayaram, John Thickstun. 4807-4818 [doi]
- Objective Bound Conditional Gaussian Process for Bayesian OptimizationTaewon Jeong, Heeyoung Kim. 4819-4828 [doi]
- Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden ConfoundingAndrew Jesson, Sören Mindermann, Yarin Gal, Uri Shalit. 4829-4838 [doi]
- DeepReDuce: ReLU Reduction for Fast Private InferenceNandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen. 4839-4849 [doi]
- Factor-analytic inverse regression for high-dimension, small-sample dimensionality reductionAditi Jha, Michael J. Morais, Jonathan W. Pillow. 4850-4859 [doi]
- Fast margin maximization via dual accelerationZiwei Ji, Nathan Srebro, Matus Telgarsky. 4860-4869 [doi]
- Marginalized Stochastic Natural Gradients for Black-Box Variational InferenceGeng Ji 0001, Debora Sujono, Erik B. Sudderth. 4870-4881 [doi]
- Bilevel Optimization: Convergence Analysis and Enhanced DesignKaiyi Ji, Junjie Yang, Yingbin Liang. 4882-4892 [doi]
- Efficient Statistical Tests: A Neural Tangent Kernel ApproachSheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba. 4893-4903 [doi]
- Scaling Up Visual and Vision-Language Representation Learning With Noisy Text SupervisionChao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig. 4904-4916 [doi]
- Multi-Dimensional Classification via Sparse Label EncodingBin-Bin Jia, Min-Ling Zhang. 4917-4926 [doi]
- Self-Damaging Contrastive LearningZiyu Jiang, Tianlong Chen, Bobak J. Mortazavi, Zhangyang Wang. 4927-4939 [doi]
- Prioritized Level ReplayMinqi Jiang, Edward Grefenstette, Tim Rocktäschel. 4940-4950 [doi]
- Monotonic Robust Policy Optimization with Model DiscrepancyYuankun Jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong. 4951-4960 [doi]
- Approximation Theory of Convolutional Architectures for Time Series ModellingHaotian Jiang, Zhong Li, Qianxiao Li. 4961-4970 [doi]
- Streaming and Distributed Algorithms for Robust Column Subset SelectionShuli Jiang, Dennis Li, Irene Mengze Li, Arvind V. Mahankali, David P. Woodruff. 4971-4981 [doi]
- Single Pass Entrywise-Transformed Low Rank ApproximationYifei Jiang, Yi Li, Yiming Sun, Jiaxin Wang, David P. Woodruff. 4982-4991 [doi]
- The Emergence of IndividualityJiechuan Jiang, Zongqing Lu. 4992-5001 [doi]
- Online Selection Problems against Constrained AdversaryZhihao Jiang, Pinyan Lu, Zhihao Gavin Tang, Yuhao Zhang 0001. 5002-5012 [doi]
- Active CoveringHeinrich Jiang, Afshin Rostamizadeh. 5013-5022 [doi]
- Emphatic Algorithms for Deep Reinforcement LearningRay Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt. 5023-5033 [doi]
- Characterizing Structural Regularities of Labeled Data in Overparameterized ModelsZiheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer. 5034-5044 [doi]
- Optimal Streaming Algorithms for Multi-Armed BanditsTianyuan Jin, Keke Huang, Jing Tang 0004, Xiaokui Xiao. 5045-5054 [doi]
- Towards Tight Bounds on the Sample Complexity of Average-reward MDPsYujia Jin, Aaron Sidford. 5055-5064 [doi]
- Almost Optimal Anytime Algorithm for Batched Multi-Armed BanditsTianyuan Jin, Jing Tang 0004, Pan Xu 0002, Keke Huang, Xiaokui Xiao, Quanquan Gu. 5065-5073 [doi]
- MOTS: Minimax Optimal Thompson SamplingTianyuan Jin, Pan Xu 0002, Jieming Shi, Xiaokui Xiao, Quanquan Gu. 5074-5083 [doi]
- Is Pessimism Provably Efficient for Offline RL?Ying Jin, Zhuoran Yang, Zhaoran Wang. 5084-5096 [doi]
- Adversarial Option-Aware Hierarchical Imitation LearningMingxuan Jing, Wenbing Huang, Fuchun Sun 0001, Xiaojian Ma, Tao Kong, Chuang Gan, Lei Li. 5097-5106 [doi]
- Discrete-Valued Latent Preference Matrix Estimation with Graph Side InformationChanghun Jo, Kangwook Lee 0001. 5107-5117 [doi]
- Provable Lipschitz Certification for Generative ModelsMatt Jordan, Alex Dimakis. 5118-5126 [doi]
- Isometric Gaussian Process Latent Variable Model for Dissimilarity DataMartin Jørgensen, Søren Hauberg. 5127-5136 [doi]
- On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel ModelsPeizhong Ju, Xiaojun Lin, Ness B. Shroff. 5137-5147 [doi]
- Improved Confidence Bounds for the Linear Logistic Model and Applications to BanditsKwang-Sung Jun, Lalit Jain, Houssam Nassif, Blake Mason. 5148-5157 [doi]
- Detection of Signal in the Spiked Rectangular ModelsJi Hyung Jung, Hye Won Chung, Ji Oon Lee. 5158-5167 [doi]
- Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine LearningYonghan Jung, Jin Tian 0001, Elias Bareinboim. 5168-5179 [doi]
- A Nullspace Property for Subspace-Preserving RecoveryMustafa Devrim Kaba, Chong You, Daniel P. Robinson, Enrique Mallada, René Vidal. 5180-5188 [doi]
- Training Recurrent Neural Networks via Forward Propagation Through TimeAnil Kag, Venkatesh Saligrama. 5189-5200 [doi]
- The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure AggregationPeter Kairouz, Ziyu Liu, Thomas Steinke 0002. 5201-5212 [doi]
- Practical and Private (Deep) Learning Without Sampling or ShufflingPeter Kairouz, Brendan McMahan, Shuang Song 0001, Om Thakkar 0001, Abhradeep Thakurta, Zheng Xu. 5213-5225 [doi]
- A Differentiable Point Process with Its Application to Spiking Neural NetworksHiroshi Kajino. 5226-5235 [doi]
- Projection techniques to update the truncated SVD of evolving matrices with applicationsVasileios Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth L. Clarkson. 5236-5246 [doi]
- Optimal Off-Policy Evaluation from Multiple Logging PoliciesNathan Kallus, Yuta Saito, Masatoshi Uehara. 5247-5256 [doi]
- Efficient Performance Bounds for Primal-Dual Reinforcement Learning from DemonstrationsAngeliki Kamoutsi, Goran Banjac, John Lygeros. 5257-5268 [doi]
- Statistical Estimation from Dependent DataVardis Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis. 5269-5278 [doi]
- SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian ProcessesSanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson. 5279-5289 [doi]
- Variational Auto-Regressive Gaussian Processes for Continual LearningSanyam Kapoor, Theofanis Karaletsos, Thang D. Bui. 5290-5300 [doi]
- Off-Policy Confidence SequencesNikos Karampatziakis, Paul Mineiro, Aaditya Ramdas. 5301-5310 [doi]
- Learning from History for Byzantine Robust OptimizationSai Praneeth Karimireddy, Lie He, Martin Jaggi. 5311-5319 [doi]
- Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio EstimationMasahiro Kato, Takeshi Teshima. 5320-5333 [doi]
- Improved Algorithms for Agnostic Pool-based Active ClassificationJulian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson. 5334-5344 [doi]
- When Does Data Augmentation Help With Membership Inference Attacks?Yigitcan Kaya, Tudor Dumitras. 5345-5355 [doi]
- Regularized Submodular Maximization at ScaleEhsan Kazemi 0001, Shervin Minaee, Moran Feldman, Amin Karbasi. 5356-5366 [doi]
- Prior Image-Constrained Reconstruction using Style-Based Generative ModelsVarun A. Kelkar, Mark A. Anastasio. 5367-5377 [doi]
- Self Normalizing FlowsT. Anderson Keller, Jorn W. T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling. 5378-5387 [doi]
- Interpretable Stability Bounds for Spectral Graph FiltersHenry Kenlay, Dorina Thanou, Xiaowen Dong 0001. 5388-5397 [doi]
- Affine Invariant Analysis of Frank-Wolfe on Strongly Convex SetsThomas Kerdreux, Lewis Liu, Simon Lacoste-Julien, Damien Scieur. 5398-5408 [doi]
- Markpainting: Adversarial Machine Learning meets InpaintingDavid Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross J. Anderson. 5409-5419 [doi]
- Finite-Sample Analysis of Off-Policy Natural Actor-Critic AlgorithmSajad Khodadadian, Zaiwei Chen, Siva Theja Maguluri. 5420-5431 [doi]
- Functional Space Analysis of Local GAN ConvergenceValentin Khrulkov, Artem Babenko, Ivan V. Oseledets. 5432-5442 [doi]
- "Hey, that's not an ODE": Faster ODE Adjoints via SeminormsPatrick Kidger, Ricky T. Q. Chen, Terry J. Lyons. 5443-5452 [doi]
- Neural SDEs as Infinite-Dimensional GANsPatrick Kidger, James Foster, Xuechen Li, Terry J. Lyons. 5453-5463 [doi]
- GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model TrainingKrishnaTeja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer. 5464-5474 [doi]
- Improving Predictors via Combination Across Diverse Task CategoriesKwang In Kim. 5475-5485 [doi]
- Self-Improved Retrosynthetic PlanningJunsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin. 5486-5495 [doi]
- Reward Identification in Inverse Reinforcement LearningKuno Kim, Shivam Garg, Kirankumar Shiragur, Stefano Ermon. 5496-5505 [doi]
- I-BERT: Integer-only BERT QuantizationSehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer. 5506-5518 [doi]
- Message Passing Adaptive Resonance Theory for Online Active Semi-supervised LearningTaeHyeong Kim, Injune Hwang, Hyundo Lee, Hyunseo Kim, Won-Seok Choi, Joseph J. Lim, Byoung-Tak Zhang. 5519-5529 [doi]
- Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-SpeechJaehyeon Kim, Jungil Kong, Juhee Son. 5530-5540 [doi]
- A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement LearningDong Ki Kim, Miao Liu 0001, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How. 5541-5550 [doi]
- Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential EquationsTimothy D. Kim, Thomas Z. Luo, Jonathan W. Pillow, Carlos Brody. 5551-5561 [doi]
- The Lipschitz Constant of Self-AttentionHyunjik Kim, George Papamakarios, Andriy Mnih. 5562-5571 [doi]
- Unsupervised Skill Discovery with Bottleneck Option LearningJaekyeom Kim, Seohong Park, Gunhee Kim. 5572-5582 [doi]
- ViLT: Vision-and-Language Transformer Without Convolution or Region SupervisionWonjae Kim, Bokyung Son, Ildoo Kim. 5583-5594 [doi]
- Bias-Robust Bayesian Optimization via Dueling BanditsJohannes Kirschner, Andreas Krause 0001. 5595-5605 [doi]
- CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and PatientsDani Kiyasseh, Tingting Zhu, David A. Clifton. 5606-5615 [doi]
- Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and MoreJohannes Klicpera, Marten Lienen, Stephan Günnemann. 5616-5627 [doi]
- Representational aspects of depth and conditioning in normalizing flowsFrederic Koehler, Viraj Mehta, Andrej Risteski. 5628-5636 [doi]
- WILDS: A Benchmark of in-the-Wild Distribution ShiftsPang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang. 5637-5664 [doi]
- One-sided Frank-Wolfe algorithms for saddle problemsVladimir Kolmogorov, Thomas Pock. 5665-5675 [doi]
- A Lower Bound for the Sample Complexity of Inverse Reinforcement LearningAbi Komanduru, Jean Honorio. 5676-5685 [doi]
- Consensus Control for Decentralized Deep LearningLingjing Kong 0001, Tao Lin 0004, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich. 5686-5696 [doi]
- A Distribution-dependent Analysis of Meta LearningMikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvári. 5697-5706 [doi]
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann. 5707-5718 [doi]
- Kernel Stein Discrepancy DescentAnna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin. 5719-5730 [doi]
- Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch SizeJack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak. 5731-5741 [doi]
- NeRF-VAE: A Geometry Aware 3D Scene Generative ModelAdam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokrá, Danilo Jimenez Rezende. 5742-5752 [doi]
- Active Testing: Sample-Efficient Model EvaluationJannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth. 5753-5763 [doi]
- High Confidence Generalization for Reinforcement LearningJames Kostas, Yash Chandak, Scott M. Jordan, Georgios Theocharous, Philip S. Thomas. 5764-5773 [doi]
- Offline Reinforcement Learning with Fisher Divergence Critic RegularizationIlya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum. 5774-5783 [doi]
- ADOM: Accelerated Decentralized Optimization Method for Time-Varying NetworksDmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander Gasnikov. 5784-5793 [doi]
- Revisiting Peng's Q(λ) for Modern Reinforcement LearningTadashi Kozuno, Yunhao Tang, Mark Rowland, Rémi Munos, Steven Kapturowski, Will Dabney, Michal Valko, David Abel. 5794-5804 [doi]
- Adapting to misspecification in contextual bandits with offline regression oraclesSanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey. 5805-5814 [doi]
- Out-of-Distribution Generalization via Risk Extrapolation (REx)David Krueger, Ethan Caballero, Jörn-Henrik Jacobsen, Amy Zhang 0001, Jonathan Binas, Dinghuai Zhang, Rémi Le Priol, Aaron C. Courville. 5815-5826 [doi]
- Near-Optimal Confidence Sequences for Bounded Random VariablesArun K. Kuchibhotla, Qinqing Zheng. 5827-5837 [doi]
- Differentially Private Bayesian Inference for Generalized Linear ModelsTejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela. 5838-5849 [doi]
- Bayesian Structural Adaptation for Continual LearningAbhishek Kumar 0001, Sunabha Chatterjee, Piyush Rai. 5850-5860 [doi]
- Implicit rate-constrained optimization of non-decomposable objectivesAbhishek Kumar, Harikrishna Narasimhan, Andrew Cotter. 5861-5871 [doi]
- A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few SamplesChristian Kümmerle, Claudio Mayrink Verdun. 5872-5883 [doi]
- Meta-Thompson SamplingBranislav Kveton, Mikhail Konobeev, Manzil Zaheer, Chih-Wei Hsu, Martin Mladenov, Craig Boutilier, Csaba Szepesvári. 5884-5893 [doi]
- Targeted Data Acquisition for Evolving Negotiation AgentsMinae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh. 5894-5904 [doi]
- ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural NetworksJungmin Kwon, Jeongseop Kim, Hyunseo Park, In Kwon Choi. 5905-5914 [doi]
- On the price of explainability for some clustering problemsEduardo Sany Laber, Lucas Murtinho. 5915-5925 [doi]
- Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian DimensionalityJonathan Lacotte, Yifei Wang, Mert Pilanci. 5926-5936 [doi]
- Generalization Bounds in the Presence of Outliers: a Median-of-Means StudyPierre Laforgue, Guillaume Staerman, Stéphan Clémençon. 5937-5947 [doi]
- Model Fusion for Personalized LearningThanh Chi Lam, Trong Nghia Hoang, Bryan Kian Hsiang Low, Patrick Jaillet. 5948-5958 [doi]
- Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant MatrixMaximilian Lam, Gu-Yeon Wei, David Brooks 0001, Vijay Janapa Reddi, Michael Mitzenmacher. 5959-5968 [doi]
- Stochastic Multi-Armed Bandits with Unrestricted Delay DistributionsTal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour. 5969-5978 [doi]
- Discovering symbolic policies with deep reinforcement learningMikel Landajuela Larma, Brenden K. Petersen, Sookyung Kim, Cláudio P. Santiago, Ruben Glatt, Nathan Mundhenk, Jacob F. Pettit, Daniel Faissol. 5979-5989 [doi]
- Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch)Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan. 5990-5999 [doi]
- Efficient Message Passing for 0-1 ILPs with Binary Decision DiagramsJan-Hendrik Lange, Paul Swoboda. 6000-6010 [doi]
- CountSketches, Feature Hashing and the Median of ThreeKasper Green Larsen, Rasmus Pagh, Jakub Tetek. 6011-6020 [doi]
- MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent SpaceSophie Laturnus, Philipp Berens. 6021-6031 [doi]
- Improved Regret Bound and Experience Replay in Regularized Policy IterationNevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvári. 6032-6042 [doi]
- LAMDA: Label Matching Deep Domain AdaptationTrung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung 0001. 6043-6054 [doi]
- Gaussian Process-Based Real-Time Learning for Safety Critical ApplicationsArmin Lederer, Alejandro Jose Ordóñez Conejo, Korbinian Maier, Wenxin Xiao, Jonas Umlauft, Sandra Hirche. 6055-6064 [doi]
- Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer TransferSeungWon Lee, Sima Behpour, Eric Eaton. 6065-6075 [doi]
- Fair Selective Classification Via SufficiencyJoshua K. Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W. Wornell. 6076-6086 [doi]
- On-the-fly Rectification for Robust Large-Vocabulary Topic InferenceMoontae Lee, Sungjun Cho, Kun Dong, David Mimno, David Bindel. 6087-6097 [doi]
- Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot ClassificationDong-Hoon Lee, Sae-Young Chung. 6098-6108 [doi]
- Continual Learning in the Teacher-Student Setup: Impact of Task SimilaritySebastian Lee, Sebastian Goldt, Andrew M. Saxe. 6109-6119 [doi]
- OptiDICE: Offline Policy Optimization via Stationary Distribution Correction EstimationJongmin Lee 0004, Wonseok Jeon, Byung-Jun Lee 0001, Joelle Pineau, Kee-Eung Kim. 6120-6130 [doi]
- SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement LearningKimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel. 6131-6141 [doi]
- Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits SimultaneouslyChung-wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang 0002. 6142-6151 [doi]
- PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-trainingKimin Lee, Laura M. Smith, Pieter Abbeel. 6152-6163 [doi]
- Near-Optimal Linear Regression under Distribution ShiftQi Lei, Wei Hu, Jason Lee. 6164-6174 [doi]
- Stability and Generalization of Stochastic Gradient Methods for Minimax ProblemsYunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying. 6175-6186 [doi]
- Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting PotJoel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel. 6187-6199 [doi]
- Better Training using Weight-Constrained Stochastic DynamicsBenedict J. Leimkuhler, Tiffany J. Vlaar, Timothée Pouchon, Amos J. Storkey. 6200-6211 [doi]
- Globally-Robust Neural NetworksKlas Leino, Zifan Wang, Matt Fredrikson. 6212-6222 [doi]
- Learning to Price Against a Moving TargetRenato Paes Leme, Balasubramanian Sivan, Yifeng Teng, Pratik Worah. 6223-6232 [doi]
- SigGPDE: Scaling Sparse Gaussian Processes on Sequential DataMaud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J. Lyons. 6233-6242 [doi]
- Strategic Classification Made PracticalSagi Levanon, Nir Rosenfeld. 6243-6253 [doi]
- 1 Certified RobustnessAlexander Levine 0001, Soheil Feizi. 6254-6264 [doi]
- BASE Layers: Simplifying Training of Large, Sparse ModelsMike Lewis, Shruti Bhosale, Tim Dettmers, Naman Goyal, Luke Zettlemoyer. 6265-6274 [doi]
- Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative ModelsJosé Lezama, Wei Chen, Qiang Qiu. 6275-6285 [doi]
- PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex OptimizationZhize Li, Hongyan Bao, Xiangliang Zhang 0001, Peter Richtárik. 6286-6295 [doi]
- Tightening the Dependence on Horizon in the Sample Complexity of Q-LearningGen Li 0005, Changxiao Cai, Yuxin Chen 0002, Yuantao Gu, Yuting Wei, Yuejie Chi. 6296-6306 [doi]
- Winograd Algorithm for AdderNetWenshuo Li, Hanting Chen, Mingqiang Huang, Xinghao Chen 0001, Chunjing Xu, Yunhe Wang 0001. 6307-6315 [doi]
- A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks CalibrationYuhang Li, Shikuang Deng, Xin Dong 0009, Ruihao Gong, Shi Gu. 6316-6325 [doi]
- Privacy-Preserving Feature Selection with Secure Multiparty ComputationXiling Li, Rafael Dowsley, Martine De Cock. 6326-6336 [doi]
- Theory of Spectral Method for Union of Subspaces-Based Random Geometry GraphGen Li 0005, Yuantao Gu. 6337-6345 [doi]
- MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement LearningKevin Li, Abhishek Gupta 0004, Ashwin Reddy, Vitchyr H. Pong, Aurick Zhou, Justin Yu, Sergey Levine. 6346-6356 [doi]
- Ditto: Fair and Robust Federated Learning Through PersonalizationTian Li 0005, Shengyuan Hu 0001, Ahmad Beirami, Virginia Smith. 6357-6368 [doi]
- Quantization Algorithms for Random Fourier FeaturesXiaoyun Li, Ping Li 0001. 6369-6380 [doi]
- Approximate Group Fairness for ClusteringBo Li, Lijun Li, Ankang Sun, Chenhao Wang, Yingfan Wang. 6381-6391 [doi]
- Sharper Generalization Bounds for ClusteringShaojie Li, Yong Liu. 6392-6402 [doi]
- Provably End-to-end Label-noise Learning without Anchor PointsXuefeng Li, Tongliang Liu, Bo Han 0003, Gang Niu 0001, Masashi Sugiyama. 6403-6413 [doi]
- A Novel Method to Solve Neural Knapsack ProblemsDuanshun Li, Jing Liu, Dongeun Lee 0001, Ali Seyedmazloom, Giridhar Kaushik, Kookjin Lee, Noseong Park. 6414-6424 [doi]
- Mixed Cross Entropy Loss for Neural Machine TranslationHaoran Li, Wei Lu. 6425-6436 [doi]
- Training Graph Neural Networks with 1000 LayersGuohao Li, Matthias Müller 0011, Bernard Ghanem, Vladlen Koltun. 6437-6449 [doi]
- Active Feature Acquisition with Generative Surrogate ModelsYang Li, Junier Oliva. 6450-6459 [doi]
- Partially Observed Exchangeable ModelingYang Li, Junier Oliva. 6460-6470 [doi]
- Testing DNN-based Autonomous Driving Systems under Critical Environmental ConditionsZhong Li, Minxue Pan, Tian Zhang, Xuandong Li. 6471-6482 [doi]
- The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with KnapsacksXiaocheng Li, Chunlin Sun, Yinyu Ye. 6483-6492 [doi]
- Distributionally Robust Optimization with Markovian DataMengmeng Li, Tobias Sutter, Daniel Kuhn. 6493-6503 [doi]
- Communication-Efficient Distributed SVD via Local Power IterationsXiang Li, Shusen Wang, Kun Chen, Zhihua Zhang. 6504-6514 [doi]
- FILTRA: Rethinking Steerable CNN by Filter TransformBo Li, Qili Wang, Gim Hee Lee. 6515-6522 [doi]
- Online Unrelated Machine Load Balancing with Predictions RevisitedShi Li 0001, Jiayi Xian. 6523-6532 [doi]
- Asymptotic Normality and Confidence Intervals for Prediction Risk of the Min-Norm Least Squares EstimatorZeng Li, Chuanlong Xie, Qinwen Wang. 6533-6542 [doi]
- TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language ModelsZhuohan Li, Siyuan Zhuang, Shiyuan Guo, Danyang Zhuo, Hao Zhang, Dawn Song, Ion Stoica. 6543-6552 [doi]
- A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and PerformanceXiaoyu Li, Zhenxun Zhuang, Francesco Orabona. 6553-6564 [doi]
- Towards Understanding and Mitigating Social Biases in Language ModelsPaul Pu Liang, Chiyu Wu, Louis-Philippe Morency, Ruslan Salakhutdinov. 6565-6576 [doi]
- Uncovering the Connections Between Adversarial Transferability and Knowledge TransferabilityKaizhao Liang, Jacky Y. Zhang, Boxin Wang, Zhuolin Yang, Sanmi Koyejo, Bo Li. 6577-6587 [doi]
- Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement LearningTung-Che Liang, Jin Zhou, Yun-Sheng Chan, Tsung-Yi Ho, Krishnendu Chakrabarty, Cy Lee. 6588-6599 [doi]
- Information Obfuscation of Graph Neural NetworksPeiyuan Liao, Han Zhao 0002, Keyulu Xu, Tommi S. Jaakkola, Geoffrey J. Gordon, Stefanie Jegelka, Ruslan Salakhutdinov. 6600-6610 [doi]
- Guided Exploration with Proximal Policy Optimization using a Single DemonstrationGabriele Libardi, Gianni De Fabritiis, Sebastian Dittert. 6611-6620 [doi]
- Debiasing a First-order Heuristic for Approximate Bi-level OptimizationValerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Quincy Davis, Adrian Weller. 6621-6630 [doi]
- Making transport more robust and interpretable by moving data through a small number of anchor pointsChi-Heng Lin, Mehdi Azabou, Eva L. Dyer. 6631-6641 [doi]
- Straight to the Gradient: Learning to Use Novel Tokens for Neural Text GenerationXiang Lin, Simeng Han, Shafiq R. Joty. 6642-6653 [doi]
- Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous DataTao Lin 0004, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi. 6654-6665 [doi]
- Generative Causal Explanations for Graph Neural NetworksWanyu Lin, Hao Lan, Baochun Li. 6666-6679 [doi]
- Tractable structured natural-gradient descent using local parameterizationsWu Lin, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt 0001. 6680-6691 [doi]
- Active Learning of Continuous-time Bayesian Networks through InterventionsDominik Linzner, Heinz Koeppl. 6692-6701 [doi]
- Phase Transitions, Distance Functions, and Implicit Neural RepresentationsYaron Lipman. 6702-6712 [doi]
- The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued RegressionFlorian List. 6713-6724 [doi]
- Understanding Instance-Level Label Noise: Disparate Impacts and TreatmentsYang Liu. 6725-6735 [doi]
- APS: Active Pretraining with Successor FeaturesHao Liu, Pieter Abbeel. 6736-6747 [doi]
- Learning by Turning: Neural Architecture Aware OptimisationYang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue. 6748-6758 [doi]
- Dynamic Game Theoretic Neural OptimizerGuan-Horng Liu, Tianrong Chen, Evangelos Theodorou. 6759-6769 [doi]
- Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual NetworksHao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao. 6770-6780 [doi]
- Just Train Twice: Improving Group Robustness without Training Group InformationEvan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn. 6781-6792 [doi]
- Event Outlier Detection in Continuous TimeSiqi Liu, Milos Hauskrecht. 6793-6803 [doi]
- Heterogeneous Risk MinimizationJiashuo Liu, Zheyuan Hu, Peng Cui 0001, Bo Li 0064, Zheyan Shen. 6804-6814 [doi]
- Stochastic Iterative Graph MatchingLinfeng Liu, Michael C. Hughes, Soha Hassoun, Liping Liu. 6815-6825 [doi]
- Cooperative Exploration for Multi-Agent Deep Reinforcement LearningIou-Jen Liu, Unnat Jain, Raymond A. Yeh, Alexander G. Schwing. 6826-6836 [doi]
- Elastic Graph Neural NetworksXiaorui Liu, Wei Jin, Yao Ma 0001, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan 0006, Jiliang Tang. 6837-6849 [doi]
- One Pass Late Fusion Multi-view ClusteringXinwang Liu, Li Liu 0002, Qing Liao 0001, Siwei Wang, Yi Zhang, Wenxuan Tu, Chang Tang, Jiyuan Liu 0003, En Zhu. 6850-6859 [doi]
- Coach-Player Multi-agent Reinforcement Learning for Dynamic Team CompositionBo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Anima Anandkumar. 6860-6870 [doi]
- From Local to Global Norm Emergence: Dissolving Self-reinforcing Substructures with Incremental Social InstrumentsYiwei Liu, Jiamou Liu, Kaibin Wan, Zhan Qin, Zijian Zhang 0001, Bakhadyr Khoussainov, Liehuang Zhu. 6871-6881 [doi]
- A Value-Function-based Interior-point Method for Non-convex Bi-level OptimizationRisheng Liu, Xuan Liu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang. 6882-6892 [doi]
- Selfish Sparse RNN TrainingShiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy. 6893-6904 [doi]
- Temporal Difference Learning as Gradient SplittingRui Liu, Alex Olshevsky. 6905-6913 [doi]
- On Robust Mean Estimation under Coordinate-level CorruptionZifan Liu, Jong Ho Park, Theodoros Rekatsinas, Christos Tzamos. 6914-6924 [doi]
- Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without SacrificesEvan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn. 6925-6935 [doi]
- How Do Adam and Training Strategies Help BNNs OptimizationZechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng. 6936-6946 [doi]
- SagaNet: A Small Sample Gated Network for Pediatric Cancer DiagnosisYuhan Liu, Shiliang Sun. 6947-6956 [doi]
- Learning Deep Neural Networks under Agnostic Corrupted SupervisionBoyang Liu, Mengying Sun, Ding Wang, Pang-Ning Tan, Jiayu Zhou. 6957-6967 [doi]
- Leveraging Public Data for Practical Private Query ReleaseTerrance Liu, Giuseppe Vietri, Thomas Steinke 0002, Jonathan R. Ullman, Zhiwei Steven Wu. 6968-6977 [doi]
- Watermarking Deep Neural Networks with Greedy ResidualsHanwen Liu, Zhenyu Weng, Yuesheng Zhu. 6978-6988 [doi]
- Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse TrainingShiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy. 6989-7000 [doi]
- A Sharp Analysis of Model-based Reinforcement Learning with Self-PlayQinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin. 7001-7010 [doi]
- Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?Ning Liu 0007, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu 0001, Yanzhi Wang. 7011-7020 [doi]
- Group Fisher Pruning for Practical Network CompressionLiyang Liu, Shilong Zhang, Zhanghui Kuang, Aojun Zhou, Jing-Hao Xue, Xinjiang Wang, Yimin Chen, Wenming Yang, Qingmin Liao, Wayne Zhang. 7021-7032 [doi]
- Infinite-Dimensional Optimization for Zero-Sum Games via Variational TransportLewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang. 7033-7044 [doi]
- Noise and Fluctuation of Finite Learning Rate Stochastic Gradient DescentKangqiao Liu, Ziyin Liu, Masahito Ueda. 7045-7056 [doi]
- Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online LearningXutong Liu 0002, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui. 7057-7066 [doi]
- Relative Positional Encoding for Transformers with Linear ComplexityAntoine Liutkus, Ondrej Cífka, Shih-Lun Wu, Umut Simsekli, Yi-Hsuan Yang, Gaël Richard. 7067-7079 [doi]
- Joint Online Learning and Decision-making via Dual Mirror DescentAlfonso Lobos, Paul Grigas, Zheng Wen. 7080-7089 [doi]
- Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian ApproachFederico López, Beatrice Pozzetti, Steve Trettel, Michael Strube 0001, Anna Wienhard. 7090-7101 [doi]
- HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network ArchitectureQian Lou, Lei Jiang 0001. 7102-7110 [doi]
- Optimal Complexity in Decentralized TrainingYucheng Lu, Christopher De Sa. 7111-7123 [doi]
- DANCE: Enhancing saliency maps using decoysYang Young Lu, Wenbo Guo 0002, Xinyu Xing, William Stafford Noble. 7124-7133 [doi]
- Binary Classification from Multiple Unlabeled Datasets via Surrogate Set ClassificationNan Lu, Shida Lei, Gang Niu 0001, Issei Sato, Masashi Sugiyama. 7134-7144 [doi]
- Variance Reduced Training with Stratified Sampling for Forecasting ModelsYucheng Lu, Youngsuk Park, Lifan Chen, Yuyang Wang, Christopher De Sa, Dean Foster. 7145-7155 [doi]
- ACE: Explaining cluster from an adversarial perspectiveYang Young Lu, Timothy C. Yu, Giancarlo Bonora, William Stafford Noble. 7156-7167 [doi]
- On Monotonic Linear Interpolation of Neural Network ParametersJames Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard S. Zemel, Roger B. Grosse. 7168-7179 [doi]
- Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range DependenciesDenis Lukovnikov, Asja Fischer. 7180-7191 [doi]
- GraphDF: A Discrete Flow Model for Molecular Graph GenerationYouzhi Luo, Keqiang Yan, Shuiwang Ji. 7192-7203 [doi]
- Trajectory Diversity for Zero-Shot CoordinationAndrei Lupu, Brandon Cui, Hengyuan Hu, Jakob N. Foerster. 7204-7213 [doi]
- HyperHyperNetwork for the Design of Antenna ArraysShahar Lutati, Lior Wolf. 7214-7223 [doi]
- Value Iteration in Continuous Actions, States and TimeMichael Lutter, Shie Mannor, Jan Peters 0001, Dieter Fox, Animesh Garg. 7224-7234 [doi]
- Meta-Cal: Well-controlled Post-hoc Calibration by RankingXingchen Ma, Matthew B. Blaschko. 7235-7245 [doi]
- Neural-Pull: Learning Signed Distance Function from Point clouds by Learning to Pull Space onto SurfaceBaorui Ma, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker. 7246-7257 [doi]
- Learning Stochastic Behaviour from Aggregate DataShaojun Ma, Shu Liu, Hongyuan Zha, Haomin Zhou 0001. 7258-7267 [doi]
- Local Algorithms for Finding Densely Connected ClustersPeter Macgregor, He Sun. 7268-7278 [doi]
- Learning to Generate Noise for Multi-Attack RobustnessDivyam Madaan, Jinwoo Shin, Sung Ju Hwang. 7279-7289 [doi]
- Learning Interaction Kernels for Agent Systems on Riemannian ManifoldsMauro Maggioni, Jason Miller, Hongda Qiu, Ming Zhong. 7290-7300 [doi]
- Tesseract: Tensorised Actors for Multi-Agent Reinforcement LearningAnuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar. 7301-7312 [doi]
- Domain Generalization using Causal MatchingDivyat Mahajan, Shruti Tople, Amit Sharma. 7313-7324 [doi]
- Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and SmoothnessVien V. Mai, Mikael Johansson 0001. 7325-7335 [doi]
- Nonparametric Hamiltonian Monte CarloCarol Mak, Fabian Zaiser, Luke Ong. 7336-7347 [doi]
- Exploiting structured data for learning contagious diseases under incomplete testingMaggie Makar, Lauren West, David Hooper, Eric Horvitz, Erica Shenoy, John V. Guttag. 7348-7357 [doi]
- Near-Optimal Algorithms for Explainable k-Medians and k-MeansKonstantin Makarychev, Liren Shan. 7358-7367 [doi]
- KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learningAshok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath. 7368-7378 [doi]
- Quantifying the Benefit of Using Differentiable Learning over Tangent KernelsEran Malach, Pritish Kamath, Emmanuel Abbe, Nathan Srebro. 7379-7389 [doi]
- Inverse Constrained Reinforcement LearningShehryar Malik, Usman Anwar, Alireza Aghasi, Ali Ahmed 0004. 7390-7399 [doi]
- A Sampling-Based Method for Tensor Ring DecompositionOsman Asif Malik, Stephen Becker. 7400-7411 [doi]
- Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond LinearityDhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li. 7412-7422 [doi]
- Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental DesignGustavo Malkomes, Bolong Cheng, Eric Hans Lee, Mike Mccourt. 7423-7434 [doi]
- Consistent Nonparametric Methods for Network Assisted Covariate EstimationXueyu Mao 0001, Deepayan Chakrabarti, Purnamrita Sarkar. 7435-7446 [doi]
- Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPsWeichao Mao, Kaiqing Zhang, Ruihao Zhu, David Simchi-Levi, Tamer Basar. 7447-7458 [doi]
- Adaptive Sampling for Best Policy Identification in Markov Decision ProcessesAymen Al Marjani, Alexandre Proutière. 7459-7468 [doi]
- Explanations for Monotonic ClassifiersJoão Marques-Silva 0001, Thomas Gerspacher, Martin C. Cooper, Alexey Ignatiev, Nina Narodytska. 7469-7479 [doi]
- Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-SolversLuke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel. 7480-7491 [doi]
- Blind Pareto Fairness and Subgroup RobustnessNatalia Martínez, Martín Bertrán, Afroditi Papadaki, Miguel R. D. Rodrigues, Guillermo Sapiro. 7492-7501 [doi]
- Necessary and sufficient conditions for causal feature selection in time series with latent common causesAtalanti-Anastasia Mastakouri, Bernhard Schölkopf, Dominik Janzing. 7502-7511 [doi]
- Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment RestrictionAfsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet. 7512-7523 [doi]
- Robust Unsupervised Learning via L-statistic MinimizationAndreas Maurer, Daniela Angela Parletta, Andrea Paudice, Massimiliano Pontil. 7524-7533 [doi]
- Adversarial Multi Class Learning under Weak Supervision with Performance GuaranteesAlessio Mazzetto, Cyrus Cousins, Dylan Sam, Stephen H. Bach, Eli Upfal. 7534-7543 [doi]
- Fundamental Tradeoffs in Distributionally Adversarial TrainingMohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup B. Rao, Tung Mai. 7544-7554 [doi]
- Leveraging Non-uniformity in First-order Non-convex OptimizationJincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvári, Dale Schuurmans. 7555-7564 [doi]
- Controlling Graph Dynamics with Reinforcement Learning and Graph Neural NetworksEli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik. 7565-7577 [doi]
- A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitionsGabriel Mel, Surya Ganguli. 7578-7587 [doi]
- Neural Architecture Search without TrainingJoe Mellor, Jack Turner, Amos J. Storkey, Elliot J. Crowley. 7588-7598 [doi]
- Fast active learning for pure exploration in reinforcement learningPierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko. 7599-7608 [doi]
- UCB Momentum Q-learning: Correcting the bias without forgettingPierre Ménard, Omar Darwiche Domingues, Xuedong Shang, Michal Valko. 7609-7618 [doi]
- An Integer Linear Programming Framework for Mining Constraints from DataTao Meng, Kai-Wei Chang. 7619-7631 [doi]
- A statistical perspective on distillationAditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Seungyeon Kim, Sanjiv Kumar. 7632-7642 [doi]
- Learn2Hop: Learned Optimization on Rough LandscapesAmil Merchant, Luke Metz, Samuel S. Schoenholz, Ekin D. Cubuk. 7643-7653 [doi]
- Counterfactual Credit Assignment in Model-Free Reinforcement LearningThomas Mesnard, Theophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas S. Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Rémi Munos. 7654-7664 [doi]
- Provably Efficient Learning of Transferable RewardsAlberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli. 7665-7676 [doi]
- Mixed Nash Equilibria in the Adversarial Examples GameLaurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre. 7677-7687 [doi]
- Learning in Nonzero-Sum Stochastic Games with PotentialsDavid Henry Mguni, Yutong Wu, Yali Du, Yaodong Yang, Ziyi Wang, Minne Li, Ying Wen, Joel Jennings, Jun Wang. 7688-7699 [doi]
- EfficientTTS: An Efficient and High-Quality Text-to-Speech ArchitectureChenfeng Miao, Shuang Liang, Zhengchen Liu, Minchuan Chen, Jun Ma, Shaojun Wang, Jing Xiao. 7700-7709 [doi]
- Outside the Echo Chamber: Optimizing the Performative RiskJohn P. Miller, Juan C. Perdomo, Tijana Zrnic. 7710-7720 [doi]
- Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution GeneralizationJohn P. Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt. 7721-7735 [doi]
- Signatured Deep Fictitious Play for Mean Field Games with Common NoiseMing Min, Ruimeng Hu. 7736-7747 [doi]
- Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech GenerationDongchan Min, Dong-Bok Lee, Eunho Yang, Sung Ju Hwang. 7748-7759 [doi]
- On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear NetworksHancheng Min, Salma Tarmoun, René Vidal, Enrique Mallada. 7760-7768 [doi]
- An Identifiable Double VAE For Disentangled RepresentationsGraziano Mita, Maurizio Filippone, Pietro Michiardi. 7769-7779 [doi]
- Offline Meta-Reinforcement Learning with Advantage WeightingEric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn. 7780-7791 [doi]
- The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy OptimizationTaiki Miyagawa, Akinori F. Ebihara. 7792-7804 [doi]
- PODS: Policy Optimization via Differentiable SimulationMiguel Zamora, Momchil Peychev, Sehoon Ha, Martin T. Vechev, Stelian Coros. 7805-7817 [doi]
- Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form GamesDustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, Amy R. Greenwald. 7818-7828 [doi]
- Neural Rough Differential Equations for Long Time SeriesJames Morrill, Cristopher Salvi, Patrick Kidger, James Foster. 7829-7838 [doi]
- Connecting Interpretability and Robustness in Decision Trees through SeparationMichal Moshkovitz, Yao-Yuan Yang, Kamalika Chaudhuri. 7839-7849 [doi]
- Outlier-Robust Optimal TransportDebarghya Mukherjee, Aritra Guha, Justin M. Solomon, Yuekai Sun, Mikhail Yurochkin. 7850-7860 [doi]
- Oblivious Sketching for Logistic RegressionAlexander Munteanu, Simon Omlor, David P. Woodruff. 7861-7871 [doi]
- Bias-Variance Reduced Local SGD for Less Heterogeneous Federated LearningTomoya Murata, Taiji Suzuki. 7872-7881 [doi]
- Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation ManifoldKieran A. Murphy, Carlos Esteves, Varun Jampani, Srikumar Ramalingam, Ameesh Makadia. 7882-7893 [doi]
- No-regret Algorithms for Capturing Events in Poisson Point ProcessesMojmir Mutny, Andreas Krause 0001. 7894-7904 [doi]
- Online Limited Memory Neural-Linear Bandits with Likelihood MatchingOfir Nabati, Tom Zahavy, Shie Mannor. 7905-7915 [doi]
- Quantitative Understanding of VAE as a Non-linearly Scaled Isometric EmbeddingAkira Nakagawa, Keizo Kato, Taiji Suzuki. 7916-7926 [doi]
- GMAC: A Distributional Perspective on Actor-Critic FrameworkDaniel Wontae Nam, Younghoon Kim, Chan Y. Park. 7927-7936 [doi]
- Memory-Efficient Pipeline-Parallel DNN TrainingDeepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia. 7937-7947 [doi]
- Randomized Dimensionality Reduction for Facility Location and Single-Linkage ClusteringShyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir. 7948-7957 [doi]
- Generating images with sparse representationsCharlie Nash, Jacob Menick, Sander Dieleman, Peter W. Battaglia. 7958-7968 [doi]
- Geometric convergence of elliptical slice samplingViacheslav Natarovskii, Daniel Rudolf, Björn Sprungk. 7969-7978 [doi]
- HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture SearchNiv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik. 7979-7990 [doi]
- Emergent Social Learning via Multi-agent Reinforcement LearningKamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques. 7991-8004 [doi]
- Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual InformationWillie Neiswanger, Ke Alexander Wang, Stefano Ermon. 8005-8015 [doi]
- Continuous Coordination As a Realistic Scenario for Lifelong LearningHadi Nekoei, Akilesh Badrinaaraayanan, Aaron C. Courville, Sarath Chandar. 8016-8024 [doi]
- Policy Caches with Successor FeaturesMark W. Nemecek, Ron Parr. 8025-8033 [doi]
- Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learnersElias Chaibub Neto. 8034-8044 [doi]
- Incentivizing Compliance with Algorithmic InstrumentsDung Daniel T. Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu 0001. 8045-8055 [doi]
- On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear WidthsQuynh Nguyen. 8056-8062 [doi]
- Value-at-Risk Optimization with Gaussian ProcessesQuoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet. 8063-8072 [doi]
- Cross-model Back-translated Distillation for Unsupervised Machine TranslationXuan-Phi Nguyen, Shafiq R. Joty, Thanh Tung Nguyen, Kui Wu 0004, Ai Ti Aw. 8073-8083 [doi]
- Optimal Transport Kernels for Sequential and Parallel Neural Architecture SearchVu Nguyen, Tam Le, Makoto Yamada, Michael A. Osborne. 8084-8095 [doi]
- Interactive Learning from Activity DescriptionKhanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto. 8096-8108 [doi]
- Nonmyopic Multifidelity Acitve SearchQuan Nguyen, Arghavan Modiri, Roman Garnett. 8109-8118 [doi]
- Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU NetworksQuynh Nguyen, Marco Mondelli, Guido F. Montúfar. 8119-8129 [doi]
- Temporal Predictive Coding For Model-Based Planning In Latent SpaceTung D. Nguyen, Rui Shu, Tuan Pham, Hung Bui, Stefano Ermon. 8130-8139 [doi]
- Differentially Private Densest Subgraph DetectionDung Nguyen, Anil Vullikanti. 8140-8151 [doi]
- Data Augmentation for Meta-LearningRenkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein. 8152-8161 [doi]
- Improved Denoising Diffusion Probabilistic ModelsAlexander Quinn Nichol, Prafulla Dhariwal. 8162-8171 [doi]
- Smooth p-Wasserstein Distance: Structure, Empirical Approximation, and Statistical ApplicationsSloan Nietert, Ziv Goldfeld, Kengo Kato. 8172-8183 [doi]
- AdaXpert: Adapting Neural Architecture for Growing DataShuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang 0004, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan. 8184-8194 [doi]
- Asynchronous Decentralized Optimization With Implicit Stochastic Variance ReductionKenta Niwa, Guoqiang Zhang 0003, W. Bastiaan Kleijn, Noboru Harada, Hiroshi Sawada, Akinori Fujino. 8195-8204 [doi]
- WGAN with an Infinitely Wide Generator Has No Spurious Stationary PointsAlbert No, Taeho Yoon, Kwon Sehyun, Ernest K. Ryu. 8205-8215 [doi]
- The Impact of Record Linkage on Learning from Feature Partitioned DataRichard Nock, Stephen Hardy 0002, Wilko Henecka, Hamish Ivey-Law, Jakub Nabaglo, Giorgio Patrini, Guillaume Smith, Brian Thorne. 8216-8226 [doi]
- Accuracy, Interpretability, and Differential Privacy via Explainable BoostingHarsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni. 8227-8237 [doi]
- Posterior Value Functions: Hindsight Baselines for Policy Gradient MethodsChris Nota, Philip Thomas, Bruno C. da Silva. 8238-8247 [doi]
- Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processesSebastian W. Ober, Laurence Aitchison. 8248-8259 [doi]
- Regularizing towards Causal Invariance: Linear Models with ProxiesMichael Oberst, Nikolaj Thams, Jonas Peters, David A. Sontag. 8260-8270 [doi]
- Sparsity-Agnostic Lasso BanditMin-hwan Oh, Garud Iyengar, Assaf Zeevi. 8271-8280 [doi]
- Autoencoder Image Interpolation by Shaping the Latent SpaceAlon Oring, Zohar Yakhini, Yacov Hel-Or. 8281-8290 [doi]
- Generalization Guarantees for Neural Architecture Search with Train-Validation SplitSamet Oymak, Mingchen Li, Mahdi Soltanolkotabi. 8291-8301 [doi]
- Vector Quantized Models for PlanningSherjil Ozair, Yazhe Li, Ali Razavi, Ioannis Antonoglou, Aäron Van Den Oord, Oriol Vinyals. 8302-8313 [doi]
- Training Adversarially Robust Sparse Networks via Bayesian Connectivity SamplingOzan Özdenizci, Robert Legenstein. 8314-8324 [doi]
- Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver HeuristicsAvik Pal, Yingbo Ma, Viral B. Shah, Christopher Vincent Rackauckas. 8325-8335 [doi]
- RNN with Particle Flow for Probabilistic Spatio-temporal ForecastingSoumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates. 8336-8348 [doi]
- Inference for Network Regression Models with Community StructureMengjie Pan, Tyler H. McCormick, Bailey K. Fosdick. 8349-8358 [doi]
- Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and ClassificationBo Pang, Ying Nian Wu. 8359-8370 [doi]
- Leveraging Good Representations in Linear Contextual BanditsMatteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta. 8371-8380 [doi]
- Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled DataSung-Woo Park, Junseok Kwon. 8381-8390 [doi]
- Unsupervised Representation Learning via Neural Activation CodingYookoon Park, Sangho Lee, Gunhee Kim, David Blei. 8391-8400 [doi]
- Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic RegressionJunhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet. 8401-8412 [doi]
- Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data GenerationSung-Woo Park, Dong Wook Shu, Junseok Kwon. 8413-8421 [doi]
- Optimal Counterfactual Explanations in Tree EnsemblesAxel Parmentier, Thibaut Vidal. 8422-8431 [doi]
- PHEW : Constructing Sparse Networks that Learn Fast and Generalize Well without Training DataShreyas Malakarjun Patil, Constantine Dovrolis. 8432-8442 [doi]
- CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming ConstraintsAnselm Paulus, Michal Rolinek, Vít Musil, Brandon Amos, Georg Martius. 8443-8453 [doi]
- Ensemble Bootstrapping for Q-LearningOren Peer, Chen Tessler, Nadav Merlis, Ron Meir. 8454-8463 [doi]
- Homomorphic Sensing: Sparsity and NoiseLiangzu Peng, Boshi Wang, Manolis C. Tsakiris. 8464-8475 [doi]
- How could Neural Networks understand Programs?Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu. 8476-8486 [doi]
- Privacy-Preserving Video Classification with Convolutional Neural NetworksSikha Pentyala, Rafael Dowsley, Martine De Cock. 8487-8499 [doi]
- Rissanen Data Analysis: Examining Dataset Characteristics via Description LengthEthan Perez, Douwe Kiela, KyungHyun Cho. 8500-8513 [doi]
- Modelling Behavioural Diversity for Learning in Open-Ended GamesNicolas Perez Nieves, Yaodong Yang, Oliver Slumbers, David Henry Mguni, Ying Wen, Jun Wang. 8514-8524 [doi]
- From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via RegularizationJulien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls. 8525-8535 [doi]
- Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational AutoencodersAdeel Pervez, Efstratios Gavves. 8536-8545 [doi]
- Differentiable Sorting Networks for Scalable Sorting and Ranking SupervisionFelix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen. 8546-8555 [doi]
- Megaverse: Simulating Embodied Agents at One Million Experiences per SecondAleksei Petrenko, Erik Wijmans, Brennan Shacklett, Vladlen Koltun. 8556-8566 [doi]
- Towards Practical Mean Bounds for Small SamplesMy Phan, Philip Thomas, Erik Learned-Miller. 8567-8576 [doi]
- DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within GibbsVincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines. 8577-8587 [doi]
- GeomCA: Geometric Evaluation of Data RepresentationsPetra Poklukar, Anastasiia Varava, Danica Kragic. 8588-8598 [doi]
- Grad-TTS: A Diffusion Probabilistic Model for Text-to-SpeechVadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail A. Kudinov. 8599-8608 [doi]
- Bias-Free Scalable Gaussian Processes via Randomized TruncationsAndres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John P. Cunningham. 8609-8619 [doi]
- Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace OffsetIlan Price, Jared Tanner. 8620-8629 [doi]
- BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale PretrainingWeizhen Qi, Yeyun Gong, Jian Jiao 0007, Yu Yan, Weizhu Chen, Dayiheng Liu, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou 0001, Nan Duan. 8630-8639 [doi]
- A Probabilistic Approach to Neural Network PruningXin Qian, Diego Klabjan. 8640-8649 [doi]
- Global Prosody Style Transfer Without Text TranscriptionsKaizhi Qian, Yang Zhang 0001, Shiyu Chang, Jinjun Xiong, Chuang Gan, David Cox, Mark Hasegawa-Johnson. 8650-8660 [doi]
- Efficient Differentiable Simulation of Articulated BodiesYi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin. 8661-8671 [doi]
- Oneshot Differentially Private Top-k SelectionGang Qiao, Weijie Su, Li Zhang. 8672-8681 [doi]
- Density Constrained Reinforcement LearningZengyi Qin, Yuxiao Chen, Chuchu Fan. 8682-8692 [doi]
- Budgeted Heterogeneous Treatment Effect EstimationTian Qin, Tian-Zuo Wang, Zhi-Hua Zhou. 8693-8702 [doi]
- Neural Transformation Learning for Deep Anomaly Detection Beyond ImagesChen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph. 8703-8714 [doi]
- Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured TransitionsShuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang. 8715-8725 [doi]
- Optimization Planning for 3D ConvNetsZhaofan Qiu, Ting Yao, Chong-Wah Ngo, Tao Mei 0001. 8726-8736 [doi]
- On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov GameShuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang. 8737-8747 [doi]
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever. 8748-8763 [doi]
- A General Framework For Detecting Anomalous Inputs to DNN ClassifiersJayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee. 8764-8775 [doi]
- Towards Open Ad Hoc Teamwork Using Graph-based Policy LearningMuhammad A. Rahman, Niklas Hopner, Filippos Christianos, Stefano V. Albrecht. 8776-8786 [doi]
- Decoupling Value and Policy for Generalization in Reinforcement LearningRoberta Raileanu, Rob Fergus. 8787-8798 [doi]
- Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation GuaranteesAnand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia M. Procopiuc, Claudio Gentile. 8799-8809 [doi]
- Differentially Private Sliced Wasserstein DistanceAlain Rakotomamonjy, Liva Ralaivola. 8810-8820 [doi]
- Zero-Shot Text-to-Image GenerationAditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever. 8821-8831 [doi]
- End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time SeriesSyama Sundar Rangapuram, Lucien D. Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski. 8832-8843 [doi]
- MSA TransformerRoshan Rao, Jason Liu, Robert Verkuil, Joshua Meier, John F. Canny, Pieter Abbeel, Tom Sercu, Alexander Rives. 8844-8856 [doi]
- Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series ForecastingKashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf. 8857-8868 [doi]
- Generative Particle Variational Inference via Estimation of Functional GradientsNeale Ratzlaff, Qinxun Bai, Fuxin Li, Wei Xu 0017. 8869-8879 [doi]
- Enhancing Robustness of Neural Networks through Fourier StabilizationNetanel Raviv, Aidan Kelley, Minzhe Guo, Yevgeniy Vorobeychik. 8880-8889 [doi]
- Disentangling Sampling and Labeling Bias for Learning in Large-output SpacesAnkit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar. 8890-8901 [doi]
- Cross-domain Imitation from ObservationsDripta S. Raychaudhuri, Sujoy Paul, Jeroen van Baar, Amit K. Roy Chowdhury. 8902-8912 [doi]
- Implicit Regularization in Tensor FactorizationNoam Razin, Asaf Maman, Nadav Cohen. 8913-8924 [doi]
- Align, then memorise: the dynamics of learning with feedback alignmentMaria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt. 8925-8935 [doi]
- Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeedMaria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborová. 8936-8947 [doi]
- Sharf: Shape-conditioned Radiance Fields from a Single ViewKonstantinos Rematas, Ricardo Martin-Brualla, Vittorio Ferrari. 8948-8958 [doi]
- LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge GraphsHongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou. 8959-8970 [doi]
- Interpreting and Disentangling Feature Components of Various Complexity from DNNsJie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang. 8971-8981 [doi]
- Integrated Defense for Resilient Graph MatchingJiaxiang Ren, Zijie Zhang, Jiayin Jin, Xin Zhao, Sixing Wu, Yang Zhou, Yelong Shen, Tianshi Che, Ruoming Jin, Dejing Dou. 8982-8997 [doi]
- Solving high-dimensional parabolic PDEs using the tensor train formatLorenz Richter, Leon Sallandt, Nikolas Nüsken. 8998-9009 [doi]
- Best Arm Identification in Graphical Bilinear BanditsGeovani Rizk, Albert Thomas 0001, Igor Colin, Rida Laraki, Yann Chevaleyre. 9010-9019 [doi]
- Principled Simplicial Neural Networks for Trajectory PredictionT. Mitchell Roddenberry, Nicholas Glaze, Santiago Segarra. 9020-9029 [doi]
- On Linear Identifiability of Learned RepresentationsGeoffrey Roeder, Luke Metz, Durk Kingma. 9030-9039 [doi]
- Representation Matters: Assessing the Importance of Subgroup Allocations in Training DataEsther Rolf, Theodora T. Worledge, Benjamin Recht, Michael I. Jordan. 9040-9051 [doi]
- TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RLClément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer. 9052-9063 [doi]
- Discretization Drift in Two-Player GamesMihaela Rosca, Yan Wu 0010, Benoit Dherin, David Barrett 0001. 9064-9074 [doi]
- On the Predictability of Pruning Across ScalesJonathan S. Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit. 9075-9083 [doi]
- Benchmarks, Algorithms, and Metrics for Hierarchical DisentanglementAndrew Slavin Ross, Finale Doshi-Velez. 9084-9094 [doi]
- Simultaneous Similarity-based Self-Distillation for Deep Metric LearningKarsten Roth, Timo Milbich, Björn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi. 9095-9106 [doi]
- Multi-group Agnostic PAC LearnabilityGuy N. Rothblum, Gal Yona. 9107-9115 [doi]
- PACOH: Bayes-Optimal Meta-Learning with PAC-GuaranteesJonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause 0001. 9116-9126 [doi]
- An Algorithm for Stochastic and Adversarial Bandits with Switching CostsChloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi. 9127-9135 [doi]
- Improving Lossless Compression Rates via Monte Carlo Bits-Back CodingYangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison. 9136-9147 [doi]
- On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian ProcessesTim G. J. Rudner, Oscar Key, Yarin Gal, Tom Rainforth. 9148-9156 [doi]
- Tilting the playing field: Dynamical loss functions for machine learningMiguel Ruiz-Garcia, Ge Zhang, Samuel S. Schoenholz, Andrea J. Liu. 9157-9167 [doi]
- UnICORNN: A recurrent model for learning very long time dependenciesT. Konstantin Rusch, Siddhartha Mishra. 9168-9178 [doi]
- Simple and Effective VAE Training with Calibrated DecodersOleh Rybkin, Kostas Daniilidis, Sergey Levine. 9179-9189 [doi]
- Model-Based Reinforcement Learning via Latent-Space CollocationOleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine. 9190-9201 [doi]
- Training Data Subset Selection for Regression with Controlled Generalization ErrorDurga Sivasubramanian, Rishabh K. Iyer, Ganesh Ramakrishnan, Abir De. 9202-9212 [doi]
- Unsupervised Part Representation by Flow CapsulesSara Sabour, Andrea Tagliasacchi, Soroosh Yazdani, Geoffrey E. Hinton, David J. Fleet. 9213-9223 [doi]
- Stochastic Sign Descent Methods: New Algorithms and Better TheoryMher Safaryan, Peter Richtárik. 9224-9234 [doi]
- Adversarial Dueling BanditsAadirupa Saha, Tomer Koren, Yishay Mansour. 9235-9244 [doi]
- Dueling Convex OptimizationAadirupa Saha, Tomer Koren, Yishay Mansour. 9245-9254 [doi]
- Optimal regret algorithm for Pseudo-1d Bandit Convex OptimizationAadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain 0002. 9255-9264 [doi]
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- Momentum Residual Neural NetworksMichael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré. 9276-9287 [doi]
- Meta-Learning Bidirectional Update RulesMark Sandler 0002, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera y Arcas. 9288-9300 [doi]
- Recomposing the Reinforcement Learning Building Blocks with HypernetworksElad Sarafian, Shai Keynan, Sarit Kraus. 9301-9312 [doi]
- Towards Understanding Learning in Neural Networks with Linear TeachersRoei Sarussi, Alon Brutzkus, Amir Globerson. 9313-9322 [doi]
- E(n) Equivariant Graph Neural NetworksVictor Garcia Satorras, Emiel Hoogeboom, Max Welling. 9323-9332 [doi]
- A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-LearningNikunj Saunshi, Arushi Gupta, Wei Hu. 9333-9343 [doi]
- Low-Rank Sinkhorn FactorizationMeyer Scetbon, Marco Cuturi, Gabriel Peyré. 9344-9354 [doi]
- Linear Transformers Are Secretly Fast Weight ProgrammersImanol Schlag, Kazuki Irie, Jürgen Schmidhuber. 9355-9366 [doi]
- Descending through a Crowded Valley - Benchmarking Deep Learning OptimizersRobin M. Schmidt, Frank Schneider, Philipp Hennig. 9367-9376 [doi]
- Equivariant message passing for the prediction of tensorial properties and molecular spectraKristof Schütt, Oliver T. Unke, Michael Gastegger. 9377-9388 [doi]
- Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning AttacksAvi Schwarzschild, Micah Goldblum, Arjun Gupta, John P. Dickerson, Tom Goldstein. 9389-9398 [doi]
- Connecting Sphere Manifolds Hierarchically for RegularizationDamien Scieur, Youngsung Kim. 9399-9409 [doi]
- Learning Intra-Batch Connections for Deep Metric LearningJenny Denise Seidenschwarz, Ismail Elezi, Laura Leal-Taixé. 9410-9421 [doi]
- Top-k eXtreme Contextual Bandits with Arm HierarchyRajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel N. Hill, Inderjit S. Dhillon. 9422-9433 [doi]
- Pure Exploration and Regret Minimization in Matching BanditsFlore Sentenac, Jialin Yi, Clément Calauzènes, Vianney Perchet, Milan Vojnovic. 9434-9442 [doi]
- State Entropy Maximization with Random Encoders for Efficient ExplorationYounggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee. 9443-9454 [doi]
- Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility SystemsPier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause 0001, Maryam Kamgarpour. 9455-9464 [doi]
- RRL: Resnet as representation for Reinforcement LearningRutav M. Shah, Vikash Kumar. 9465-9476 [doi]
- Equivariant Networks for Pixelized SpheresMehran Shakerinava, Siamak Ravanbakhsh. 9477-9488 [doi]
- Personalized Federated Learning using HypernetworksAviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik. 9489-9502 [doi]
- On the Power of Localized Perceptron for Label-Optimal Learning of Halfspaces with Adversarial NoiseJie Shen. 9503-9514 [doi]
- Sample-Optimal PAC Learning of Halfspaces with Malicious NoiseJie Shen. 9515-9524 [doi]
- Backdoor Scanning for Deep Neural Networks through K-Arm OptimizationGuangyu Shen, Yingqi Liu, Guanhong Tao, Shengwei An, Qiuling Xu, Siyuan Cheng 0005, ShiQing Ma, Xiangyu Zhang 0001. 9525-9536 [doi]
- State Relevance for Off-Policy EvaluationSimon P. Shen, Yecheng Ma, Omer Gottesman, Finale Doshi-Velez. 9537-9546 [doi]
- SparseBERT: Rethinking the Importance Analysis in Self-attentionHan Shi, Jiahui Gao, Xiaozhe Ren, Hang Xu, Xiaodan Liang, Zhenguo Li, James Tin-Yau Kwok. 9547-9557 [doi]
- Learning Gradient Fields for Molecular Conformation GenerationChence Shi, Shitong Luo, Minkai Xu, Jian Tang. 9558-9568 [doi]
- Segmenting Hybrid Trajectories using Latent ODEsRuian Shi, Quaid Morris. 9569-9579 [doi]
- Deeply-Debiased Off-Policy Interval EstimationChengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song. 9580-9591 [doi]
- GANMEX: One-vs-One Attributions using GAN-based Model ExplainabilitySheng-Min Shih, Pin-Ju Tien, Zohar Karnin. 9592-9602 [doi]
- Large-Scale Meta-Learning with Continual Trajectory ShiftingJaewoong Shin, Haebeom Lee, Boqing Gong, Sung Ju Hwang. 9603-9613 [doi]
- AGENT: A Benchmark for Core Psychological ReasoningTianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin A. Smith, Shari Liu, Dan Gutfreund, Elizabeth S. Spelke, Joshua B. Tenenbaum, Tomer Ullman. 9614-9625 [doi]
- Zoo-Tuning: Adaptive Transfer from A Zoo of ModelsYang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long. 9626-9637 [doi]
- Aggregating From Multiple Target-Shifted SourcesChangjian Shui, Zijian Li 0001, Jiaqi Li, Christian Gagné, Charles X. Ling, Boyu Wang 0004. 9638-9648 [doi]
- Testing Group Fairness via Optimal Transport ProjectionsNian Si, Karthyek Murthy, Jose H. Blanchet, Viet Anh Nguyen. 9649-9659 [doi]
- On Characterizing GAN Convergence Through Proximal Duality GapSahil Sidheekh, Aroof Aimen, Narayanan C. Krishnan. 9660-9670 [doi]
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- Directed Graph Embeddings in Pseudo-Riemannian ManifoldsAaron Sim, Maciej Wiatrak, Angus Brayne, Páidí Creed, Saee Paliwal. 9681-9690 [doi]
- Collaborative Bayesian Optimization with Fair RegretRachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet. 9691-9701 [doi]
- Dynamic Planning and Learning under Recovering RewardsDavid Simchi-Levi, Zeyu Zheng, Feng Zhu. 9702-9711 [doi]
- PopSkipJump: Decision-Based Attack for Probabilistic ClassifiersCarl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause. 9712-9721 [doi]
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- Structured World Belief for Reinforcement Learning in POMDPGautam Singh, Skand Vishwanath Peri, Junghyun Kim, Hyunseok Kim, Sungjin Ahn. 9744-9755 [doi]
- Skew Orthogonal ConvolutionsSahil Singla 0002, Soheil Feizi. 9756-9766 [doi]
- Multi-Task Reinforcement Learning with Context-based RepresentationsShagun Sodhani, Amy Zhang 0001, Joelle Pineau. 9767-9779 [doi]
- Shortest-Path Constrained Reinforcement Learning for Sparse Reward TasksSungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee. 9780-9790 [doi]
- Accelerating Feedforward Computation via Parallel Nonlinear Equation SolvingYang Song, Chenlin Meng, Renjie Liao, Stefano Ermon. 9791-9800 [doi]
- PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided ExplorationYuda Song, Wen Sun. 9801-9811 [doi]
- Fast Sketching of Polynomial Kernels of Polynomial DegreeZhao Song 0002, David P. Woodruff, Zheng Yu, Lichen Zhang. 9812-9823 [doi]
- Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-SumsChaobing Song, Stephen J. Wright, Jelena Diakonikolas. 9824-9834 [doi]
- Oblivious Sketching-based Central Path Method for Linear ProgrammingZhao Song 0002, Zheng Yu. 9835-9847 [doi]
- Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation LearningSumedh A. Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf. 9848-9858 [doi]
- Decomposed Mutual Information Estimation for Contrastive Representation LearningAlessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoffrey J. Gordon, Philip Bachman, Remi Tachet des Combes. 9859-9869 [doi]
- Decoupling Representation Learning from Reinforcement LearningAdam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin. 9870-9879 [doi]
- K-shot NAS: Learnable Weight-Sharing for NAS with K-shot SupernetsXiu Su, Shan You, Mingkai Zheng, Fei Wang 0032, Chen Qian 0006, Changshui Zhang, Chang Xu 0002. 9880-9890 [doi]
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- Not All Memories are Created Equal: Learning to Forget by ExpiringSainbayar Sukhbaatar, Da Ju, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan. 9902-9912 [doi]
- Nondeterminism and Instability in Neural Network OptimizationCecilia Summers, Michael J. Dinneen. 9913-9922 [doi]
- AutoSampling: Search for Effective Data Sampling SchedulesMing Sun, Haoxuan Dou, Baopu Li, Junjie Yan, Wanli Ouyang, Lei Cui. 9923-9933 [doi]
- What Makes for End-to-End Object Detection?Peize Sun, Yi Jiang, Enze Xie, Wenqi Shao, Zehuan Yuan, Changhu Wang, Ping Luo. 9934-9944 [doi]
- DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-LearningWei-Fang Sun, Cheng-Kuang Lee, Chun-Yi Lee. 9945-9954 [doi]
- Scalable Variational Gaussian Processes via Harmonic Kernel DecompositionShengyang Sun, Jiaxin Shi, Andrew Gordon Wilson, Roger B. Grosse. 9955-9965 [doi]
- Reasoning Over Virtual Knowledge Bases With Open Predicate RelationsHaitian Sun, Patrick Verga, Bhuwan Dhingra, Ruslan Salakhutdinov, William W. Cohen. 9966-9977 [doi]
- PAC-Learning for Strategic ClassificationRavi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao. 9978-9988 [doi]
- Reinforcement Learning for Cost-Aware Markov Decision ProcessesWesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu 0001, David Kraemer. 9989-9999 [doi]
- Model-Targeted Poisoning Attacks with Provable ConvergenceFnu Suya, Saeed Mahloujifar, Anshuman Suri, David Evans 0001, Yuan Tian 0001. 10000-10010 [doi]
- Generalization Error Bound for Hyperbolic Ordinal EmbeddingAtsushi Suzuki, Atsushi Nitanda, Jing Wang 0023, Linchuan Xu, Kenji Yamanishi, Marc Cavazza. 10011-10021 [doi]
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- Parallel tempering on optimized pathsSaifuddin Syed, Vittorio Romaniello, Trevor Campbell, Alexandre Bouchard-Côté. 10033-10042 [doi]
- Robust Representation Learning via Perceptual Similarity MetricsSaeid Asgari Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal. 10043-10053 [doi]
- DriftSurf: Stable-State / Reactive-State Learning under Concept DriftAshraf Tahmasbi, Ellango Jothimurugesan, Srikanta Tirthapura, Phillip B. Gibbons. 10054-10064 [doi]
- Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-TrainingKai Sheng Tai, Peter Bailis, Gregory Valiant. 10065-10075 [doi]
- Approximation Theory Based Methods for RKHS BanditsSho Takemori, Masahiro Sato. 10076-10085 [doi]
- Supervised Tree-Wasserstein DistanceYuki Takezawa, Ryoma Sato, Makoto Yamada. 10086-10095 [doi]
- EfficientNetV2: Smaller Models and Faster TrainingMingxing Tan, Quoc V. Le. 10096-10106 [doi]
- SGA: A Robust Algorithm for Partial Recovery of Tree-Structured Graphical Models with Noisy SamplesAnshoo Tandon, Aldric H. J. Han, Vincent Y. F. Tan. 10107-10117 [doi]
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- Taylor Expansion of Discount FactorsYunhao Tang, Mark Rowland, Rémi Munos, Michal Valko. 10130-10140 [doi]
- REPAINT: Knowledge Transfer in Deep Reinforcement LearningYunzhe Tao, Sahika Genc, Jonathan Chung, Tao Sun, Sunil Mallya. 10141-10152 [doi]
- Understanding the Dynamics of Gradient Flow in Overparameterized Linear modelsSalma Tarmoun, Guilherme França, Benjamin D. Haeffele, René Vidal. 10153-10161 [doi]
- Sequential Domain Adaptation by Synthesizing Distributionally Robust ExpertsBahar Taskesen, Man-Chung Yue, Jose H. Blanchet, Daniel Kuhn, Viet Anh Nguyen. 10162-10172 [doi]
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- SGLB: Stochastic Gradient Langevin BoostingAleksei Ustimenko, Liudmila Prokhorenkova. 10487-10496 [doi]
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- Principal Component Hierarchy for Sparse Quadratic ProgramsRobbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari, Peyman Mohajerin Esfahani. 10607-10616 [doi]
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- A Proxy Variable View of Shared ConfoundingYixin Wang, David M. Blei. 10697-10707 [doi]
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- Explainable Automated Graph Representation Learning with Hyperparameter ImportanceXin Wang 0019, Shuyi Fan, Kun Kuang, Wenwu Zhu 0001. 10727-10737 [doi]
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- Label Distribution Learning MachineJing Wang, Xin Geng. 10749-10759 [doi]
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- Directional Bias AmplificationAngelina Wang, Olga Russakovsky. 10882-10893 [doi]
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- Characterizing the Gap Between Actor-Critic and Policy GradientJunfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans. 11101-11111 [doi]
- Toward Understanding the Feature Learning Process of Self-supervised Contrastive LearningZixin Wen, Yuanzhi Li. 11112-11122 [doi]
- Keyframe-Focused Visual Imitation LearningChuan Wen, Jierui Lin, Jianing Qian, Yang Gao 0029, Dinesh Jayaraman. 11123-11133 [doi]
- Learning de-identified representations of prosody from raw audioJack Weston, Raphael Lenain, Udeepa Meepegama, Emil Fristed. 11134-11145 [doi]
- Solving Inverse Problems with a Flow-based Noise ModelJay Whang, Qi Lei, Alex Dimakis. 11146-11157 [doi]
- Composing Normalizing Flows for Inverse ProblemsJay Whang, Erik M. Lindgren, Alex Dimakis. 11158-11169 [doi]
- Which transformer architecture fits my data? A vocabulary bottleneck in self-attentionNoam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua. 11170-11181 [doi]
- Prediction-Centric Learning of Independent Cascade Dynamics from Partial ObservationsMateusz Wilinski, Andrey Y. Lokhov. 11182-11192 [doi]
- Leveraging Language to Learn Program Abstractions and Search HeuristicsCatherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas. 11193-11204 [doi]
- Leveraging Sparse Linear Layers for Debuggable Deep NetworksEric Wong, Shibani Santurkar, Aleksander Madry. 11205-11216 [doi]
- Learning Neural Network SubspacesMitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari. 11217-11227 [doi]
- Conjugate Energy-Based ModelsHao Wu 0020, Babak Esmaeili, Michael L. Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent. 11228-11239 [doi]
- Making Paper Reviewing Robust to Bid Manipulation AttacksRuihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger. 11240-11250 [doi]
- LIME: Learning Inductive Bias for Primitives of Mathematical ReasoningYuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy. 11251-11262 [doi]
- ChaCha for Online AutoMLQingyun Wu, Chi Wang 0001, John Langford 0001, Paul Mineiro, Marco Rossi 0009. 11263-11273 [doi]
- Temporally Correlated Task Scheduling for Sequence LearningXueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie 0003, Tao Qin, Tie-Yan Liu. 11274-11284 [doi]
- Class2Simi: A Noise Reduction Perspective on Learning with Noisy LabelsSonghua Wu, Xiaobo Xia, Tongliang Liu, Bo Han 0003, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu 0001. 11285-11295 [doi]
- On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDPTianhao Wu, Yunchang Yang, Simon S. Du, Liwei Wang 0001. 11296-11306 [doi]
- Generative Video Transformer: Can Objects be the Words?Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn. 11307-11318 [doi]
- Uncertainty Weighted Actor-Critic for Offline Reinforcement LearningYue Wu 0001, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang 0050, Ruslan Salakhutdinov, Hanlin Goh. 11319-11328 [doi]
- Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering ApproachQitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan Zha. 11329-11339 [doi]
- Data-efficient Hindsight Off-policy Option LearningMarkus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller. 11340-11350 [doi]
- A Bit More Bayesian: Domain-Invariant Learning with UncertaintyZehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao 0001, Cees Snoek. 11351-11361 [doi]
- On the Optimality of Batch Policy Optimization AlgorithmsChenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li 0001, Csaba Szepesvári, Dale Schuurmans. 11362-11371 [doi]
- CRFL: Certifiably Robust Federated Learning against Backdoor AttacksChulin Xie, Minghao Chen 0001, Pin-Yu Chen, Bo Li. 11372-11382 [doi]
- RNNRepair: Automatic RNN Repair via Model-based AnalysisXiaofei Xie, Wenbo Guo 0002, Lei Ma, Wei Le, Jian Wang, Lingjun Zhou, Yang Liu, Xinyu Xing. 11383-11392 [doi]
- Deep Reinforcement Learning amidst Continual Structured Non-StationarityAnnie Xie, James Harrison, Chelsea Finn. 11393-11403 [doi]
- Batch Value-function Approximation with Only RealizabilityTengyang Xie, Nan Jiang. 11404-11413 [doi]
- Interaction-Grounded LearningTengyang Xie, John Langford 0001, Paul Mineiro, Ida Momennejad. 11414-11423 [doi]
- Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved GeneralizationSang Michael Xie, Tengyu Ma, Percy Liang. 11424-11435 [doi]
- Learning While Playing in Mean-Field Games: Convergence and OptimalityQiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca. 11436-11447 [doi]
- Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve GeneralizationZeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama. 11448-11458 [doi]
- A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex OptimizationRan Xin, Usman A. Khan, Soummya Kar. 11459-11469 [doi]
- Explore Visual Concept Formation for Image ClassificationShengzhou Xiong, Yihua Tan, Guoyou Wang. 11470-11479 [doi]
- CRPO: A New Approach for Safe Reinforcement Learning with Convergence GuaranteeTengyu Xu, Yingbin Liang, Guanghui Lan. 11480-11491 [doi]
- To be Robust or to be Fair: Towards Fairness in Adversarial TrainingHan Xu, Xiaorui Liu, Yaxin Li, Anil K. Jain 0001, Jiliang Tang. 11492-11501 [doi]
- Interpretable Stein Goodness-of-fit Tests on Riemannian ManifoldWenkai Xu, Takeru Matsuda. 11502-11513 [doi]
- Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical PerspectivesDa Xu, Chuanwei Ruan, Evren Körpeoglu, Sushant Kumar, Kannan Achan. 11514-11524 [doi]
- Dash: Semi-Supervised Learning with Dynamic ThresholdingYi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yu-Feng Li, Baigui Sun, Hao Li, Rong Jin. 11525-11536 [doi]
- An End-to-End Framework for Molecular Conformation Generation via Bilevel ProgrammingMinkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gómez-Bombarelli, Jian Tang. 11537-11547 [doi]
- Self-supervised Graph-level Representation Learning with Local and Global StructureMinghao Xu, Hang Wang, Bingbing Ni, Hongyu Guo, Jian Tang. 11548-11558 [doi]
- Conformal prediction interval for dynamic time-seriesChen Xu, Yao Xie 0002. 11559-11569 [doi]
- Learner-Private Convex OptimizationJiaming Xu, Kuang Xu, Dana Yang. 11570-11580 [doi]
- Doubly Robust Off-Policy Actor-Critic: Convergence and OptimalityTengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin Liang. 11581-11591 [doi]
- Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More DepthKeyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi. 11592-11602 [doi]
- Group-Sparse Matrix Factorization for Transfer Learning of Word EmbeddingsKan Xu, Xuanyi Zhao, Hamsa Bastani, Osbert Bastani. 11603-11612 [doi]
- KNAS: Green Neural Architecture SearchJingjing Xu, Liang Zhao, Junyang Lin, Rundong Gao, Xu Sun 0001, Hongxia Yang. 11613-11625 [doi]
- Structured Convolutional Kernel Networks for Airline Crew SchedulingYassine Yaakoubi, François Soumis, Simon Lacoste-Julien. 11626-11636 [doi]
- Mediated Uncoupled Learning: Learning Functions without Direct Input-output CorrespondencesIkko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama. 11637-11647 [doi]
- EL-Attention: Memory Efficient Lossless Attention for GenerationYu Yan, Jiusheng Chen, Weizhen Qi, Nikhil Bhendawade, Yeyun Gong, Nan Duan, Ruofei Zhang. 11648-11658 [doi]
- Link Prediction with Persistent Homology: An Interactive ViewZuoYu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen 0012. 11659-11669 [doi]
- CATE: Computation-aware Neural Architecture Encoding with TransformersShen Yan, Kaiqiang Song, Fei Liu, Mi Zhang 0002. 11670-11681 [doi]
- On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training FrameworkZeyu Yan, Fei Wen, Rendong Ying, Chao Ma, Peilin Liu. 11682-11692 [doi]
- CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature SelectionHanshu Yan, Jingfeng Zhang, Gang Niu 0001, Jiashi Feng, Vincent Y. F. Tan, Masashi Sugiyama. 11693-11703 [doi]
- Exact Gap between Generalization Error and Uniform Convergence in Random Feature ModelsZitong Yang, Yu Bai, Song Mei. 11704-11715 [doi]
- Learning Optimal Auctions with Correlated Valuations from SamplesChunxue Yang, Xiaohui Bei. 11716-11726 [doi]
- Tensor Programs IV: Feature Learning in Infinite-Width Neural NetworksGreg Yang, Edward J. Hu. 11727-11737 [doi]
- LARNet: Lie Algebra Residual Network for Face RecognitionXiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan 0001, Zhifeng Li, Wei Liu. 11738-11750 [doi]
- BASGD: Buffered Asynchronous SGD for Byzantine LearningYi-Rui Yang, Wu-Jun Li. 11751-11761 [doi]
- Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training DynamicsGreg Yang, Etai Littwin. 11762-11772 [doi]
- Graph Neural Networks Inspired by Classical Iterative AlgorithmsYongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf. 11773-11783 [doi]
- Representation Matters: Offline Pretraining for Sequential Decision MakingMengjiao Yang, Ofir Nachum. 11784-11794 [doi]
- Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline PoliciesTsung-Yen Yang, Justinian Rosca, Karthik Narasimhan, Peter J. Ramadge. 11795-11807 [doi]
- Voice2Series: Reprogramming Acoustic Models for Time Series ClassificationChao-Han Huck Yang, Yun-Yun Tsai, Pin-Yu Chen. 11808-11819 [doi]
- When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUCZhiyong Yang 0001, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang. 11820-11829 [doi]
- Rethinking Rotated Object Detection with Gaussian Wasserstein Distance LossXue Yang 0005, Junchi Yan, Qi Ming, Wentao Wang, Xiaopeng Zhang, Qi Tian 0001. 11830-11841 [doi]
- Delving into Deep Imbalanced RegressionYuzhe Yang, Kaiwen Zha, Ying-Cong Chen, Hao Wang, Dina Katabi. 11842-11851 [doi]
- Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural NetworksYukun Yang, Wenrui Zhang, Peng Li. 11852-11862 [doi]
- SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural NetworksLingxiao Yang, Ru-Yuan Zhang, Lida Li, Xiaohua Xie. 11863-11874 [doi]
- HAWQ-V3: Dyadic Neural Network QuantizationZhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang 0001, Yida Wang, Michael W. Mahoney, Kurt Keutzer. 11875-11886 [doi]
- Improving Generalization in Meta-learning via Task AugmentationHuaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei 0001, Li Tian, James Zou, JunZhou Huang, Zhenhui Li. 11887-11897 [doi]
- Deep Learning for Functional Data Analysis with Adaptive Basis LayersJunwen Yao, Jonas Mueller, Jane-ling Wang. 11898-11908 [doi]
- Addressing Catastrophic Forgetting in Few-Shot ProblemsPau Ching Yap, Hippolyt Ritter, David Barber. 11909-11919 [doi]
- Reinforcement Learning with Prototypical RepresentationsDenis Yarats, Rob Fergus, Alessandro Lazaric, Lerrel Pinto. 11920-11931 [doi]
- Elementary superexpressive activationsDmitry Yarotsky. 11932-11940 [doi]
- Break-It-Fix-It: Unsupervised Learning for Program RepairMichihiro Yasunaga, Percy Liang. 11941-11952 [doi]
- Improving Gradient Regularization using Complex-Valued Neural NetworksEric C. Yeats, Yiran Chen, Hai Li. 11953-11963 [doi]
- Neighborhood Contrastive Learning Applied to Online Patient MonitoringHugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch. 11964-11974 [doi]
- From Local Structures to Size Generalization in Graph Neural NetworksGilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron. 11975-11986 [doi]
- Improved OOD Generalization via Adversarial Training and PretraingMingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma. 11987-11997 [doi]
- Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term ConstraintsXinlei Yi, Xiuxian Li, Tao Yang 0003, Lihua Xie, Tianyou Chai, Karl Henrik Johansson. 11998-12008 [doi]
- Continuous-time Model-based Reinforcement LearningCagatay Yildiz, Markus Heinonen, Harri Lähdesmäki. 12009-12018 [doi]
- Distributed Nyström Kernel Learning with CommunicationsRong Yin 0001, Weiping Wang, Dan Meng. 12019-12028 [doi]
- Path Planning using Neural A* SearchRyo Yonetani, Tatsunori Taniai, Mohammadamin Barekatain, Mai Nishimura, Asako Kanezaki. 12029-12039 [doi]
- SinIR: Efficient General Image Manipulation with Single Image ReconstructionJihyeong Yoo, Qifeng Chen. 12040-12050 [doi]
- Conditional Temporal Neural Processes with Covariance LossBoseon Yoo, Jiwoo Lee, Janghoon Ju, Seijun Chung, Soyeon Kim, Jaesik Choi. 12051-12061 [doi]
- Adversarial Purification with Score-based Generative ModelsJongmin Yoon, Sung Ju Hwang, Juho Lee. 12062-12072 [doi]
- Federated Continual Learning with Weighted Inter-client TransferJaehong Yoon, Wonyong Jeong, Giwoong Lee, Eunho Yang, Sung Ju Hwang. 12073-12086 [doi]
- Autoencoding Under Normalization ConstraintsSangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park. 12087-12097 [doi]
- Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient NormTaeho Yoon, Ernest K. Ryu. 12098-12109 [doi]
- Lower-Bounded Proper Losses for Weakly Supervised ClassificationShuhei M. Yoshida, Takashi Takenouchi, Masashi Sugiyama. 12110-12120 [doi]
- Graph Contrastive Learning AutomatedYuning You, Tianlong Chen, Yang Shen, Zhangyang Wang. 12121-12132 [doi]
- LogME: Practical Assessment of Pre-trained Models for Transfer LearningKaichao You, Yong Liu, Jianmin Wang, Mingsheng Long. 12133-12143 [doi]
- Exponentially Many Local Minima in Quantum Neural NetworksXuchen You, Xiaodi Wu. 12144-12155 [doi]
- DAGs with No Curl: An Efficient DAG Structure Learning ApproachYue Yu, Tian Gao, Naiyu Yin, Qiang Ji. 12156-12166 [doi]
- Provably Efficient Algorithms for Multi-Objective Competitive RLTiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra. 12167-12176 [doi]
- Whittle Networks: A Deep Likelihood Model for Time SeriesZhongjie Yu 0001, Fabrizio G. Ventola, Kristian Kersting. 12177-12186 [doi]
- Deep Latent Graph MatchingTianshu Yu, Runzhong Wang, Junchi Yan, Baoxin Li. 12187-12197 [doi]
- Learning Generalized Intersection Over Union for Dense Pixelwise PredictionJiaqian Yu, Jingtao Xu, Yiwei Chen, Weiming Li, Qiang Wang, ByungIn Yoo, Jae-Joon Han. 12198-12207 [doi]
- Large Scale Private Learning via Low-rank ReparametrizationDa Yu, Huishuai Zhang, Wei Chen, Jian Yin 0001, Tie-Yan Liu. 12208-12218 [doi]
- Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication ComplexityZhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang. 12219-12229 [doi]
- Neural Tangent Generalization AttacksChia-Hung Yuan, Shan-Hung Wu. 12230-12240 [doi]
- On Explainability of Graph Neural Networks via Subgraph ExplorationsHao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji. 12241-12252 [doi]
- Federated Composite OptimizationHonglin Yuan, Manzil Zaheer, Sashank J. Reddi. 12253-12266 [doi]
- Three Operator Splitting with a Nonconvex Loss FunctionAlp Yurtsever, Varun Mangalick, Suvrit Sra. 12267-12277 [doi]
- Grey-box Extraction of Natural Language ModelsSantiago Zanella Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf. 12278-12286 [doi]
- Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RLAndrea Zanette. 12287-12297 [doi]
- Learning Binary Decision Trees by Argmin DifferentiationValentina Zantedeschi, Matt J. Kusner, Vlad Niculae. 12298-12309 [doi]
- Barlow Twins: Self-Supervised Learning via Redundancy ReductionJure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stéphane Deny. 12310-12320 [doi]
- You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli SamplingZhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn M. Fung, Vikas Singh. 12321-12332 [doi]
- DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement LearningDaochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu. 12333-12344 [doi]
- DORO: Distributional and Outlier Robust OptimizationRuntian Zhai, Chen Dan 0001, J. Zico Kolter, Pradeep Ravikumar. 12345-12355 [doi]
- Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang 0001, Aaron C. Courville. 12356-12367 [doi]
- Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist NeuronsBohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang. 12368-12379 [doi]
- Efficient Lottery Ticket Finding: Less Data is MoreZhenyu Zhang, Xuxi Chen, Tianlong Chen, Zhangyang Wang. 12380-12390 [doi]
- Robust Policy Gradient against Strong Data CorruptionXuezhou Zhang, Yiding Chen, Xiaojin Zhu 0001, Wen Sun. 12391-12401 [doi]
- Near Optimal Reward-Free Reinforcement LearningZihan Zhang, Simon Du, Xiangyang Ji. 12402-12412 [doi]
- Bayesian Attention Belief NetworksShujian Zhang, Xinjie Fan, Bo Chen 0001, Mingyuan Zhou. 12413-12426 [doi]
- Understanding Failures in Out-of-Distribution Detection with Deep Generative ModelsLily H. Zhang, Mark Goldstein, Rajesh Ranganath. 12427-12436 [doi]
- Poolingformer: Long Document Modeling with Pooling AttentionHang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv 0001, Nan Duan, Weizhu Chen. 12437-12446 [doi]
- Probabilistic Generating CircuitsHonghua Zhang, Brendan Juba, Guy Van den Broeck. 12447-12457 [doi]
- PAPRIKA: Private Online False Discovery Rate ControlWanrong Zhang, Gautam Kamath 0001, Rachel Cummings. 12458-12467 [doi]
- Learning from Noisy Labels with No Change to the Training ProcessMingyuan Zhang, Jane Lee, Shivani Agarwal 0001. 12468-12478 [doi]
- Progressive-Scale Boundary Blackbox Attack via Projective Gradient EstimationJiawei Zhang, Linyi Li, Huichen Li, Xiaolu Zhang, Shuang Yang, Bo Li. 12479-12490 [doi]
- FOP: Factorizing Optimal Joint Policy of Maximum-Entropy Multi-Agent Reinforcement LearningTianhao Zhang, Yueheng Li, Chen Wang, Guangming Xie, Zongqing Lu. 12491-12500 [doi]
- Learning Noise Transition Matrix from Only Noisy Labels via Total Variation RegularizationYivan Zhang, Gang Niu 0001, Masashi Sugiyama. 12501-12512 [doi]
- Quantile Bandits for Best Arms IdentificationMengyan Zhang, Cheng Soon Ong. 12513-12523 [doi]
- Towards Better Robust Generalization with Shift Consistency RegularizationShufei Zhang, Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Rui Zhang 0012, Xinping Yi. 12524-12534 [doi]
- On-Policy Deep Reinforcement Learning for the Average-Reward CriterionYiming Zhang 0010, Keith W. Ross. 12535-12545 [doi]
- Differentiable Dynamic Quantization with Mixed Precision and Adaptive ResolutionZhaoyang Zhang, Wenqi Shao, Jinwei Gu, Xiaogang Wang 0001, Ping Luo. 12546-12556 [doi]
- iDARTS: Differentiable Architecture Search with Stochastic Implicit GradientsMiao Zhang, Steven W. Su, Shirui Pan, Xiaojun Chang, M. Ehsan Abbasnejad, Reza Haffari. 12557-12566 [doi]
- Deep Coherent Exploration for Continuous ControlYijie Zhang, Herke van Hoof. 12567-12577 [doi]
- Average-Reward Off-Policy Policy Evaluation with Function ApproximationShangtong Zhang, Yi Wan, Richard S. Sutton, Shimon Whiteson. 12578-12588 [doi]
- Matrix Sketching for Secure Collaborative Machine LearningMengjiao Zhang, Shusen Wang. 12589-12599 [doi]
- MetaCURE: Meta Reinforcement Learning with Empowerment-Driven ExplorationJin Zhang, Jianhao Wang, Hao Hu, Tong Chen, Yingfeng Chen, Changjie Fan, Chongjie Zhang. 12600-12610 [doi]
- World Model as a Graph: Learning Latent Landmarks for PlanningLunjun Zhang, Ge Yang 0003, Bradly C. Stadie. 12611-12620 [doi]
- Breaking the Deadly Triad with a Target NetworkShangtong Zhang, Hengshuai Yao, Shimon Whiteson. 12621-12631 [doi]
- Multiscale Invertible Generative Networks for High-Dimensional Bayesian InferenceShumao Zhang, Pengchuan Zhang, Thomas Y. Hou. 12632-12641 [doi]
- Meta Learning for Support Recovery in High-dimensional Precision Matrix EstimationQian Zhang, Yilin Zheng, Jean Honorio. 12642-12652 [doi]
- Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample ComplexityZihan Zhang, Yuan Zhou 0007, Xiangyang Ji. 12653-12662 [doi]
- Learning to Rehearse in Long Sequence MemorizationZhu Zhang, Chang Zhou, Jianxin Ma, Zhijie Lin, Jingren Zhou, Hongxia Yang, Zhou Zhao. 12663-12673 [doi]
- Dataset Condensation with Differentiable Siamese AugmentationBo Zhao, Hakan Bilen. 12674-12685 [doi]
- Joining datasets via data augmentation in the label space for neural networksJunbo Zhao, Mingfeng Ou, Linji Xue, Yunkai Cui, Sai Wu, Gang Chen 0001. 12686-12696 [doi]
- Calibrate Before Use: Improving Few-shot Performance of Language ModelsZihao Zhao, Eric Wallace, Shi Feng, Dan Klein, Sameer Singh 0001. 12697-12706 [doi]
- Few-Shot Neural Architecture SearchYiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo 0001. 12707-12718 [doi]
- Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial AttacksXin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan 0001. 12719-12735 [doi]
- Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech TranslationRenjie Zheng, Junkun Chen, Mingbo Ma, Liang Huang 0001. 12736-12746 [doi]
- Two Heads are Better Than One: Hypergraph-Enhanced Graph Reasoning for Visual Event RatiocinationWenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang 0001. 12747-12760 [doi]
- How Framelets Enhance Graph Neural NetworksXuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang 0001, Pietro Lió, Ming Li 0065, Guido Montúfar. 12761-12771 [doi]
- Probabilistic Sequential Shrinking: A Best Arm Identification Algorithm for Stochastic Bandits with CorruptionsZixin Zhong, Wang Chi Cheung, Vincent Y. F. Tan. 12772-12781 [doi]
- Towards Distraction-Robust Active Visual TrackingFangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang 0001. 12782-12792 [doi]
- Provably Efficient Reinforcement Learning for Discounted MDPs with Feature MappingDongruo Zhou, Jiafan He, Quanquan Gu. 12793-12802 [doi]
- Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty EstimationAurick Zhou, Sergey Levine. 12803-12812 [doi]
- Optimal Estimation of High Dimensional Smooth Additive Function Based on Noisy ObservationsFan Zhou, Ping Li 0001. 12813-12823 [doi]
- Incentivized Bandit Learning with Self-Reinforcing User PreferencesTianchen Zhou, Jia Liu, Chaosheng Dong, Jingyuan Deng. 12824-12834 [doi]
- Towards Defending against Adversarial Examples via Attack-Invariant FeaturesDawei Zhou, Tongliang Liu, Bo Han 0003, Nannan Wang, Chunlei Peng, Xinbo Gao 0001. 12835-12845 [doi]
- Asymmetric Loss Functions for Learning with Noisy LabelsXiong Zhou, Xianming Liu, Junjun Jiang, Xin Gao, Xiangyang Ji. 12846-12856 [doi]
- Examining and Combating Spurious Features under Distribution ShiftChunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig. 12857-12867 [doi]
- Sparse and Imperceptible Adversarial Attack via a Homotopy AlgorithmMingkang Zhu, Tianlong Chen, Zhangyang Wang. 12868-12877 [doi]
- Data-Free Knowledge Distillation for Heterogeneous Federated LearningZhuangdi Zhu, Junyuan Hong, Jiayu Zhou. 12878-12889 [doi]
- Spectral vertex sparsifiers and pair-wise spanners over distributed graphsChunjiang Zhu, Qinqing Liu, Jinbo Bi. 12890-12900 [doi]
- Few-shot Language Coordination by Modeling Theory of MindHao Zhu, Graham Neubig, Yonatan Bisk. 12901-12911 [doi]
- Clusterability as an Alternative to Anchor Points When Learning with Noisy LabelsZhaowei Zhu, Yiwen Song, Yang Liu. 12912-12923 [doi]
- Commutative Lie Group VAE for Disentanglement LearningXinqi Zhu, Chang Xu, Dacheng Tao. 12924-12934 [doi]
- Accumulated Decoupled Learning with Gradient Staleness Mitigation for Convolutional Neural NetworksHuiping Zhuang, Zhenyu Weng, Fulin Luo, Kar-Ann Toj, Haizhou Li 0001, Zhiping Lin. 12935-12944 [doi]
- Demystifying Inductive Biases for (Beta-)VAE Based ArchitecturesDominik Zietlow, Michal Rolinek, Georg Martius. 12945-12954 [doi]
- Recovering AES Keys with a Deep Cold Boot AttackItamar Zimerman, Eliya Nachmani, Lior Wolf. 12955-12966 [doi]
- Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement LearningMatthieu Zimmer, Claire Glanois, Umer Siddique, Paul Weng. 12967-12978 [doi]
- Contrastive Learning Inverts the Data Generating ProcessRoland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel. 12979-12990 [doi]
- Exploration in Approximate Hyper-State Space for Meta Reinforcement LearningLuisa M. Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson. 12991-13001 [doi]
- Provable Robustness of Adversarial Training for Learning Halfspaces with NoiseDifan Zou, Spencer Frei, Quanquan Gu. 13002-13011 [doi]
- On the Convergence of Hamiltonian Monte Carlo with Stochastic GradientsDifan Zou, Quanquan Gu. 13012-13022 [doi]
- A Functional Perspective on Learning Symmetric Functions with Neural NetworksAaron Zweig, Joan Bruna. 13023-13032 [doi]