Abstract is missing.
- Selective Dyna-Style Planning Under Limited Model CapacityZaheer Abbas, Samuel Sokota, Erin Talvitie, Martha White. 1-10 [doi]
- A distributional view on multi-objective policy optimizationAbbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller. 11-22 [doi]
- Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian RelaxationMarc Abeille, Alessandro Lazaric. 23-31 [doi]
- Super-efficiency of automatic differentiation for functions defined as a minimumPierre Ablin, Gabriel Peyré, Thomas Moreau. 32-41 [doi]
- A Geometric Approach to Archetypal Analysis via Sparse ProjectionsVinayak Abrol, Pulkit Sharma. 42-51 [doi]
- Context Aware Local Differential PrivacyJayadev Acharya, Kallista Bonawitz, Peter Kairouz, Daniel Ramage, Ziteng Sun. 52-62 [doi]
- Efficient Intervention Design for Causal Discovery with LatentsRaghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco. 63-73 [doi]
- The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of GeneralizationBen Adlam, Jeffrey Pennington. 74-84 [doi]
- Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial CorruptionsArpit Agarwal 0001, Shivani Agarwal, Sanjeev Khanna, Prathamesh Patil. 85-95 [doi]
- Boosting for Control of Dynamical SystemsNaman Agarwal, Nataly Brukhim, Elad Hazan, Zhou Lu. 96-103 [doi]
- An Optimistic Perspective on Offline Reinforcement LearningRishabh Agarwal, Dale Schuurmans, Mohammad Norouzi 0002. 104-114 [doi]
- Optimal Bounds between f-Divergences and Integral Probability MetricsRohit Agrawal 0002, Thibaut Horel. 115-124 [doi]
- LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing ExperimentsAli AhmadiTeshnizi, Saber Salehkaleybar, Negar Kiyavash. 125-133 [doi]
- Learning What to Defer for Maximum Independent SetsSungsoo Ahn, Younggyo Seo, Jinwoo Shin. 134-144 [doi]
- Invariant Risk Minimization GamesKartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar. 145-155 [doi]
- Why bigger is not always better: on finite and infinite neural networksLaurence Aitchison. 156-164 [doi]
- Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence FunctionsAhmed M. Alaa, Mihaela van der Schaar. 165-174 [doi]
- Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence FunctionsAhmed M. Alaa, Mihaela van der Schaar. 175-190 [doi]
- Random extrapolation for primal-dual coordinate descentAhmet Alacaoglu, Olivier Fercoq, Volkan Cevher. 191-201 [doi]
- A new regret analysis for Adam-type algorithmsAhmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher. 202-210 [doi]
- Restarted Bayesian Online Change-point Detector achieves Optimal Detection DelayRéda Alami, Odalric Maillard, Raphaël Féraud. 211-221 [doi]
- Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift AdaptationAmr Alexandari, Anshul Kundaje, Avanti Shrikumar. 222-232 [doi]
- The Implicit Regularization of Stochastic Gradient Flow for Least SquaresAlnur Ali, Edgar Dobriban, Ryan J. Tibshirani. 233-244 [doi]
- Structural Language Models of CodeUri Alon 0002, Roy Sadaka, Omer Levy, Eran Yahav. 245-256 [doi]
- LowFER: Low-rank Bilinear Pooling for Link PredictionSaadullah Amin, Stalin Varanasi, Katherine Ann Dunfield, Günter Neumann. 257-268 [doi]
- Discount Factor as a Regularizer in Reinforcement LearningRon Amit, Ron Meir, Kamil Ciosek. 269-278 [doi]
- Neuro-Symbolic Visual Reasoning: DisentanglingSaeed Amizadeh, Hamid Palangi, Alex Polozov, Yichen Huang, Kazuhito Koishida. 279-290 [doi]
- The Differentiable Cross-Entropy MethodBrandon Amos, Denis Yarats. 291-302 [doi]
- Customizing ML Predictions for Online AlgorithmsKeerti Anand, Rong Ge, Debmalya Panigrahi. 303-313 [doi]
- Fairwashing explanations with off-manifold detergentChristopher J. Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-Robert Müller, Pan Kessel. 314-323 [doi]
- Population-Based Black-Box Optimization for Biological Sequence DesignChristof Angermüller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy Colwell, D. Sculley. 324-334 [doi]
- Low-loss connection of weight vectors: distribution-based approachesIvan Anokhin, Dmitry Yarotsky. 335-344 [doi]
- Online metric algorithms with untrusted predictionsAntonios Antoniadis, Christian Coester, Marek Eliás, Adam Polak 0001, Bertrand Simon. 345-355 [doi]
- NADS: Neural Architecture Distribution Search for Uncertainty AwarenessRandy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian. 356-366 [doi]
- Provable Representation Learning for Imitation Learning via Bi-level OptimizationSanjeev Arora, Simon S. Du, Sham M. Kakade, Yuping Luo, Nikunj Saunshi. 367-376 [doi]
- Quantum BoostingSrinivasan Arunachalam, Reevu Maity. 377-387 [doi]
- Black-box Certification and Learning under Adversarial PerturbationsHassan Ashtiani, Vinayak Pathak, Ruth Urner. 388-398 [doi]
- Invertible generative models for inverse problems: mitigating representation error and dataset biasMuhammad Asim, Max Daniels, Oscar Leong, Ali Ahmed, Paul Hand. 399-409 [doi]
- On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic SettingsMahmoud Assran, Mike Rabbat. 410-420 [doi]
- Safe screening rules for L0-regression from Perspective RelaxationsAlper Atamtürk, Andres Gomez. 421-430 [doi]
- Adversarial Learning Guarantees for Linear Hypotheses and Neural NetworksPranjal Awasthi, Natalie Frank, Mehryar Mohri. 431-441 [doi]
- Sample Amplification: Increasing Dataset Size even when Learning is ImpossibleBrian Axelrod, Shivam Garg 0001, Vatsal Sharan, Gregory Valiant. 442-451 [doi]
- Sparse Convex Optimization via Adaptively Regularized Hard ThresholdingKyriakos Axiotis, Maxim Sviridenko. 452-462 [doi]
- Model-Based Reinforcement Learning with Value-Targeted RegressionAlex Ayoub, Zeyu Jia, Csaba Szepesvári, Mengdi Wang, Lin Yang. 463-474 [doi]
- Forecasting Sequential Data Using Consistent Koopman AutoencodersOmri Azencot, N. Benjamin Erichson, Vanessa Lin, Michael W. Mahoney. 475-485 [doi]
- Constant Curvature Graph Convolutional NetworksGregor Bachmann, Gary Bécigneul, Octavian Ganea. 486-496 [doi]
- Scalable Nearest Neighbor Search for Optimal TransportArturs Backurs, Yihe Dong, Piotr Indyk, Ilya P. Razenshteyn, Tal Wagner. 497-506 [doi]
- Agent57: Outperforming the Atari Human BenchmarkAdrià Puigdomènech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Charles Blundell. 507-517 [doi]
- Fiduciary BanditsGal Bahar, Omer Ben-Porat, Kevin Leyton-Brown, Moshe Tennenholtz. 518-527 [doi]
- Learning De-biased Representations with Biased RepresentationsHyojin Bahng, Sanghyuk Chun, Sangdoo Yun, Jaegul Choo, Seong Joon Oh. 528-539 [doi]
- Deep k-NN for Noisy LabelsDara Bahri, Heinrich Jiang, Maya R. Gupta. 540-550 [doi]
- Provable Self-Play Algorithms for Competitive Reinforcement LearningYu Bai, Chi Jin. 551-560 [doi]
- Sparse Subspace Clustering with Entropy-NormLiang Bai, Jiye Liang. 561-568 [doi]
- Coresets for Clustering in Graphs of Bounded TreewidthDaniel Baker, Vladimir Braverman, Lingxiao Huang, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu 0002. 569-579 [doi]
- Refined bounds for algorithm configuration: The knife-edge of dual class approximabilityMaria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik. 580-590 [doi]
- Ready Policy One: World Building Through Active LearningPhilip Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen J. Roberts. 591-601 [doi]
- Stochastic Optimization for Regularized Wasserstein EstimatorsMarin Ballu, Quentin Berthet, Francis R. Bach. 602-612 [doi]
- Dual Mirror Descent for Online Allocation ProblemsSantiago R. Balseiro, Haihao Lu, Vahab S. Mirrokni. 613-628 [doi]
- Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous ClustersSubho S. Banerjee, Saurabh Jha, Zbigniew Kalbarczyk, Ravishankar K. Iyer. 629-641 [doi]
- UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-TrainingHangbo Bao, Li Dong 0004, Furu Wei, Wenhui Wang, Nan Yang 0002, Xiaodong Liu, Yu Wang 0009, Jianfeng Gao, Songhao Piao, Ming Zhou 0001, Hsiao-Wuen Hon. 642-652 [doi]
- Fast OSCAR and OWL Regression via Safe Screening RulesRunxue Bao, Bin Gu, Heng Huang. 653-663 [doi]
- Option Discovery in the Absence of Rewards with Manifold AnalysisAmitay Bar, Ronen Talmon, Ron Meir. 664-674 [doi]
- Learning the piece-wise constant graph structure of a varying Ising modelBatiste Le Bars, Pierre Humbert, Argyris Kalogeratos, Nicolas Vayatis. 675-684 [doi]
- Frequency Bias in Neural Networks for Input of Non-Uniform DensityRonen Basri, Meirav Galun, Amnon Geifman, David W. Jacobs, Yoni Kasten, Shira Kritchman. 685-694 [doi]
- Private Query Release Assisted by Public DataRaef Bassily, Albert Cheu, Shay Moran, Aleksandar Nikolov, Jonathan R. Ullman, Steven Z. Wu. 695-703 [doi]
- ECLIPSE: An Extreme-Scale Linear Program Solver for Web-ApplicationsKinjal Basu 0001, Amol Ghoting, Rahul Mazumder, Yao Pan. 704-714 [doi]
- On Second-Order Group Influence Functions for Black-Box PredictionsSamyadeep Basu, Xuchen You, Soheil Feizi. 715-724 [doi]
- Kernel interpolation with continuous volume samplingAyoub Belhadji, Rémi Bardenet, Pierre Chainais. 725-735 [doi]
- Decoupled Greedy Learning of CNNsEugene Belilovsky, Michael Eickenberg, Edouard Oyallon. 736-745 [doi]
- The Cost-free Nature of Optimally Tuning Tikhonov Regularizers and Other Ordered SmoothersPierre Bellec, Dana Yang. 746-755 [doi]
- Defense Through Diverse DirectionsChristopher M. Bender, Yang Li 0012, Yifeng Shi, Michael K. Reiter, Junier Oliva. 756-766 [doi]
- Interference and Generalization in Temporal Difference LearningEmmanuel Bengio, Joelle Pineau, Doina Precup. 767-777 [doi]
- Preselection BanditsViktor Bengs, Eyke Hüllermeier. 778-787 [doi]
- Efficient Policy Learning from Surrogate-Loss Classification ReductionsAndrew Bennett, Nathan Kallus. 788-798 [doi]
- Training Neural Networks for and by InterpolationLeonard Berrada, Andrew Zisserman, M. Pawan Kumar. 799-809 [doi]
- Implicit differentiation of Lasso-type models for hyperparameter optimizationQuentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon. 810-821 [doi]
- Online Learning with Imperfect HintsAditya Bhaskara, Ashok Cutkosky, Ravi Kumar 0001, Manish Purohit. 822-831 [doi]
- When are Non-Parametric Methods Robust?Robi Bhattacharjee, Kamalika Chaudhuri. 832-841 [doi]
- Learning and Sampling of Atomic Interventions from ObservationsArnab Bhattacharyya 0001, Sutanu Gayen, Saravanan Kandasamy 0002, Ashwin Maran, N. Variyam Vinodchandran. 842-853 [doi]
- Near-optimal sample complexity bounds for learning Latent k-polytopes and applications to Ad-MixturesChiranjib Bhattacharyya, Ravindran Kannan. 854-863 [doi]
- Low-Rank Bottleneck in Multi-head Attention ModelsSrinadh Bhojanapalli, Chulhee Yun, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar. 864-873 [doi]
- Spectral Clustering with Graph Neural Networks for Graph PoolingFilippo Maria Bianchi, Daniele Grattarola, Cesare Alippi. 874-883 [doi]
- Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden ConfoundersIoana Bica, Ahmed M. Alaa, Mihaela van der Schaar. 884-895 [doi]
- Adversarial Robustness for CodePavol Bielik, Martin T. Vechev. 896-907 [doi]
- The Boomerang SamplerJoris Bierkens, Sebastiano Grazzi, Kengo Kamatani, Gareth Roberts. 908-918 [doi]
- Tight Bounds on Minimax Regret under Logarithmic Loss via Self-ConcordanceBlair Bilodeau, Dylan J. Foster, Daniel M. Roy 0001. 919-929 [doi]
- My Fair Bandit: Distributed Learning of Max-Min Fairness with Multi-player BanditsIlai Bistritz, Tavor Z. Baharav, Amir Leshem, Nicholas Bambos. 930-940 [doi]
- Provable guarantees for decision tree induction: the agnostic settingGuy Blanc, Jane Lange, Li-Yang Tan. 941-949 [doi]
- Fast Differentiable Sorting and RankingMathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga. 950-959 [doi]
- Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry. 960-969 [doi]
- Modulating Surrogates for Bayesian OptimizationErik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill W. Campbell, Carl Henrik Ek. 970-979 [doi]
- Deep Coordination GraphsWendelin Boehmer, Vitaly Kurin, Shimon Whiteson. 980-991 [doi]
- Lorentz Group Equivariant Neural Network for Particle PhysicsAlexander Bogatskiy, Brandon M. Anderson, Jan T. Offermann, Marwah Roussi, David W. Miller, Risi Kondor. 992-1002 [doi]
- Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and MoreAleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann. 1003-1013 [doi]
- Proper Network Interpretability Helps Adversarial Robustness in ClassificationAkhilan Boopathy, Sijia Liu 0001, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel. 1014-1023 [doi]
- Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural NetworksBlake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan. 1024-1034 [doi]
- Small Data, Big Decisions: Model Selection in the Small-Data RegimeJörg Bornschein, Francesco Visin, Simon Osindero. 1035-1044 [doi]
- Latent Variable Modelling with Hyperbolic Normalizing FlowsAvishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton. 1045-1055 [doi]
- Tightening Exploration in Upper Confidence Reinforcement LearningHippolyte Bourel, Odalric Maillard, Mohammad Sadegh Talebi. 1056-1066 [doi]
- Preference Modeling with Context-Dependent Salient FeaturesAmanda Bower, Laura Balzano. 1067-1077 [doi]
- Adversarial Filters of Dataset BiasesRonan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, Yejin Choi. 1078-1088 [doi]
- Calibration, Entropy Rates, and Memory in Language ModelsMark Braverman, Xinyi Chen, Sham M. Kakade, Karthik Narasimhan, Cyril Zhang, Yi Zhang. 1089-1099 [doi]
- Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye DimensionVladimir Braverman, Robert Krauthgamer, Aditya Krishnan 0001, Roi Sinoff. 1100-1110 [doi]
- All in the Exponential Family: Bregman Duality in Thermodynamic Variational InferenceRob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan. 1111-1122 [doi]
- Estimating the Number and Effect Sizes of Non-null HypothesesJennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson. 1123-1133 [doi]
- The FAST Algorithm for Submodular MaximizationAdam Breuer, Eric Balkanski, Yaron Singer. 1134-1143 [doi]
- GNN-FiLM: Graph Neural Networks with Feature-wise Linear ModulationMarc Brockschmidt. 1144-1152 [doi]
- TaskNorm: Rethinking Batch Normalization for Meta-LearningJohn Bronskill, Jonathan Gordon 0003, James Requeima, Sebastian Nowozin, Richard E. Turner. 1153-1164 [doi]
- Safe Imitation Learning via Fast Bayesian Reward Inference from PreferencesDaniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum. 1165-1177 [doi]
- A Pairwise Fair and Community-preserving Approach to k-Center ClusteringBrian Brubach, Darshan Chakrabarti, John P. Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas. 1178-1189 [doi]
- Scalable Exact Inference in Multi-Output Gaussian ProcessesWessel Bruinsma, Eric Perim, William Tebbutt, J. Scott Hosking, Arno Solin, Richard E. Turner. 1190-1201 [doi]
- Online Pricing with Offline Data: Phase Transition and Inverse Square LawJinzhi Bu, David Simchi-Levi, Yunzong Xu. 1202-1210 [doi]
- Empirical Study of the Benefits of Overparameterization in Learning Latent Variable ModelsRares-Darius Buhai, Yoni Halpern, Yoon Kim, Andrej Risteski, David A. Sontag. 1211-1219 [doi]
- DeBayes: a Bayesian Method for Debiasing Network EmbeddingsMaarten Buyl, Tijl De Bie. 1220-1229 [doi]
- Structured Prediction with Partial Labelling through the Infimum LossVivien Cabannes, Alessandro Rudi, Francis R. Bach. 1230-1239 [doi]
- Online Learned Continual Compression with Adaptive Quantization ModulesLucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau. 1240-1250 [doi]
- Boosted Histogram Transform for RegressionYuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin. 1251-1261 [doi]
- On Validation and Planning of An Optimal Decision Rule with Application in Healthcare StudiesHengrui Cai, Wenbin Lu, Rui Song. 1262-1270 [doi]
- Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimalityChangxiao Cai, H. Vincent Poor, Yuxin Chen 0002. 1271-1282 [doi]
- Provably Efficient Exploration in Policy OptimizationQi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang. 1283-1294 [doi]
- Near-linear time Gaussian process optimization with adaptive batching and resparsificationDaniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco. 1295-1305 [doi]
- Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label RatesJeff Calder, Brendan Cook, Matthew Thorpe, Dejan Slepcev. 1306-1316 [doi]
- Explore, Discover and Learn: Unsupervised Discovery of State-Covering SkillsVictor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giró i Nieto, Jordi Torres. 1317-1327 [doi]
- Logarithmic Regret for Learning Linear Quadratic Regulators EfficientlyAsaf Cassel, Alon Cohen, Tomer Koren. 1328-1337 [doi]
- Fully Parallel Hyperparameter Search: Reshaped Space-FillingMarie-Liesse Cauwet, Camille Couprie, Julien Dehos, Pauline Luc, Jérémy Rapin, Morgane Rivière, Fabien Teytaud, Olivier Teytaud, Nicolas Usunier. 1338-1348 [doi]
- Data preprocessing to mitigate bias: A maximum entropy based approachL. Elisa Celis, Vijay Keswani, Nisheeth K. Vishnoi. 1349-1359 [doi]
- Meta-learning with Stochastic Linear BanditsLeonardo Cella, Alessandro Lazaric, Massimiliano Pontil. 1360-1370 [doi]
- Description Based Text Classification with Reinforcement LearningDuo Chai, Wei Wu, Qinghong Han, Fei Wu, Jiwei Li. 1371-1382 [doi]
- Concise Explanations of Neural Networks using Adversarial TrainingPrasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury 0001, Xi Wu 0001, Somesh Jha. 1383-1391 [doi]
- Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate ShiftAlex J. Chan, Ahmed M. Alaa, Zhaozhi Qian, Mihaela van der Schaar. 1392-1402 [doi]
- Imputer: Sequence Modelling via Imputation and Dynamic ProgrammingWilliam Chan, Chitwan Saharia, Geoffrey E. Hinton, Mohammad Norouzi 0002, Navdeep Jaitly. 1403-1413 [doi]
- Optimizing for the Future in Non-Stationary MDPsYash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas. 1414-1425 [doi]
- Learning to Simulate and Design for Structural EngineeringKai-Hung Chang, Chin-Yi Cheng. 1426-1436 [doi]
- Decentralized Reinforcement Learning: Global Decision-Making via Local Economic TransactionsMichael Chang 0003, Sidhant Kaushik, S. Matthew Weinberg, Tom Griffiths, Sergey Levine. 1437-1447 [doi]
- Invariant RationalizationShiyu Chang, Yang Zhang, Mo Yu, Tommi S. Jaakkola. 1448-1458 [doi]
- Circuit-Based Intrinsic Methods to Detect OverfittingSatrajit Chatterjee, Alan Mishchenko. 1459-1468 [doi]
- Better depth-width trade-offs for neural networks through the lens of dynamical systemsVaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas. 1469-1478 [doi]
- Explainable and Discourse Topic-aware Neural Language UnderstandingYatin Chaudhary, Hinrich Schütze, Pankaj Gupta. 1479-1488 [doi]
- Uncertainty-Aware Lookahead Factor Models for Quantitative InvestingLakshay Chauhan, John Alberg, Zachary C. Lipton. 1489-1499 [doi]
- Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint ReasoningDi Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John M. Gregoire, Carla P. Gomes. 1500-1509 [doi]
- Self-PU: Self Boosted and Calibrated Positive-Unlabeled TrainingXuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gong, Kewei Chen 0001, Zhangyang Wang. 1510-1519 [doi]
- Learning To Stop While Learning To PredictXinshi Chen, Hanjun Dai, Yu Li 0006, Xin Gao, Le Song. 1520-1530 [doi]
- Combinatorial Pure Exploration for Dueling BanditWei Chen, Yihan Du, Longbo Huang, Haoyu Zhao. 1531-1541 [doi]
- Graph Optimal Transport for Cross-Domain AlignmentLiqun Chen, Zhe Gan, Yu Cheng 0001, Linjie Li, Lawrence Carin, Jingjing Liu 0001. 1542-1553 [doi]
- Stabilizing Differentiable Architecture Search via Perturbation-based RegularizationXiangning Chen, Cho-Jui Hsieh. 1554-1565 [doi]
- Mapping natural-language problems to formal-language solutions using structured neural representationsKezhen Chen, Qiuyuan Huang, Hamid Palangi, Paul Smolensky, Kenneth D. Forbus, Jianfeng Gao. 1566-1575 [doi]
- Convolutional Kernel Networks for Graph-Structured DataDexiong Chen, Laurent Jacob, Julien Mairal. 1576-1586 [doi]
- Learning Flat Latent Manifolds with VAEsNutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt. 1587-1596 [doi]
- A Simple Framework for Contrastive Learning of Visual RepresentationsTing Chen, Simon Kornblith, Mohammad Norouzi 0002, Geoffrey E. Hinton. 1597-1607 [doi]
- Retro*: Learning Retrosynthetic Planning with Neural Guided A* SearchBinghong Chen, Chengtao Li, Hanjun Dai, Le Song. 1608-1616 [doi]
- Differentiable Product Quantization for End-to-End Embedding CompressionTing Chen, Lala Li, Yizhou Sun. 1617-1626 [doi]
- On Efficient Constructions of CheckpointsYu Chen 0036, Zhenming Liu, Bin Ren, Xin Jin. 1627-1636 [doi]
- Angular Visual HardnessBeidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar. 1637-1648 [doi]
- Estimating the Error of Randomized Newton Methods: A Bootstrap ApproachJessie X. T. Chen, Miles E. Lopes. 1649-1659 [doi]
- VFlow: More Expressive Generative Flows with Variational Data AugmentationJianfei Chen 0001, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian 0001. 1660-1669 [doi]
- More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard ModelsLin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi. 1670-1680 [doi]
- An Accelerated DFO Algorithm for Finite-sum Convex FunctionsYuwen Chen, Antonio Orvieto, Aurélien Lucchi. 1681-1690 [doi]
- Generative Pretraining From PixelsMark Chen, Alec Radford, Rewon Child, Jeffrey Wu 0003, Heewoo Jun, David Luan, Ilya Sutskever. 1691-1703 [doi]
- Negative Sampling in Semi-Supervised learningJohn Chen, Vatsal Shah, Anastasios Kyrillidis. 1704-1714 [doi]
- Optimization from Structured Samples for Coverage FunctionsWei Chen 0013, Xiaoming Sun, Jialin Zhang, Zhijie Zhang. 1715-1724 [doi]
- Simple and Deep Graph Convolutional NetworksMing Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, Yaliang Li. 1725-1735 [doi]
- On Breaking Deep Generative Model-based Defenses and BeyondYanzhi Chen, Renjie Xie, Zhanxing Zhu. 1736-1745 [doi]
- Automated Synthetic-to-Real GeneralizationWuyang Chen, Zhiding Yu, Zhangyang Wang, Animashree Anandkumar. 1746-1756 [doi]
- (Locally) Differentially Private Combinatorial Semi-BanditsXiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Liwei Wang. 1757-1767 [doi]
- High-dimensional Robust Mean Estimation via Gradient DescentYu Cheng 0002, Ilias Diakonikolas, Rong Ge 0001, Mahdi Soltanolkotabi. 1768-1778 [doi]
- CLUB: A Contrastive Log-ratio Upper Bound of Mutual InformationPengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin. 1779-1788 [doi]
- Learning with Bounded Instance and Label-dependent Label NoiseJiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao, Dacheng Tao. 1789-1799 [doi]
- Mutual Transfer Learning for Massive DataChing-Wei Cheng, Xingye Qiao, Guang Cheng. 1800-1809 [doi]
- Stochastic Gradient and Langevin ProcessesXiang Cheng, Dong Yin, Peter L. Bartlett, Michael I. Jordan. 1810-1819 [doi]
- Representation Learning via Adversarially-Contrastive Optimal TransportAnoop Cherian, Shuchin Aeron. 1820-1830 [doi]
- Convergence Rates of Variational Inference in Sparse Deep LearningBadr-Eddine Chérief-Abdellatif. 1831-1842 [doi]
- Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) OptimismWang Chi Cheung, David Simchi-Levi, Ruihao Zhu. 1843-1854 [doi]
- Streaming Coresets for Symmetric Tensor FactorizationRachit Chhaya, Jayesh Choudhari, Anirban Dasgupta 0001, Supratim Shit. 1855-1865 [doi]
- On Coresets for Regularized RegressionRachit Chhaya, Anirban Dasgupta 0001, Supratim Shit. 1866-1876 [doi]
- How to Solve Fair k-Center in Massive Data ModelsAshish Chiplunkar, Sagar Kale, Sivaramakrishnan Natarajan Ramamoorthy. 1877-1886 [doi]
- Fair Generative Modeling via Weak SupervisionKristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon. 1887-1898 [doi]
- Encoding Musical Style with Transformer AutoencodersKristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, Jesse H. Engel. 1899-1908 [doi]
- k-means++: few more steps yield constant approximationDavin Choo, Christoph Grunau, Julian Portmann, Václav Rozhon. 1909-1917 [doi]
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- Scalable Deep Generative Modeling for Sparse GraphsHanjun Dai, Azade Nazi, Yujia Li, Bo Dai, Dale Schuurmans. 2302-2312 [doi]
- The Usual Suspects? Reassessing Blame for VAE Posterior CollapseBin Dai, Ziyu Wang 0006, David P. Wipf. 2313-2322 [doi]
- Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference SettingNiccolò Dalmasso, Rafael Izbicki, Ann B. Lee. 2323-2334 [doi]
- Goodness-of-Fit Tests for Inhomogeneous Random GraphsSoham Dan, Bhaswar B. Bhattacharya. 2335-2344 [doi]
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- Interpreting Robust Optimization via Adversarial Influence FunctionsZhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang. 2464-2473 [doi]
- Non-convex Learning via Replica Exchange Stochastic Gradient MCMCWei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin. 2474-2483 [doi]
- Towards Understanding the Dynamics of the First-Order AdversariesZhun Deng, Hangfeng He, Jiaoyang Huang, Weijie J. Su. 2484-2493 [doi]
- Robust Pricing in Dynamic Mechanism DesignYuan Deng, Sébastien Lahaie, Vahab S. Mirrokni. 2494-2503 [doi]
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- Enhancing Simple Models by Exploiting What They Already KnowAmit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss. 2525-2534 [doi]
- Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear ConvergenceLijun Ding, Yingjie Fei, Qiantong Xu, Chengrun Yang. 2535-2544 [doi]
- Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal FeaturesLiang Ding, Rui Tuo, Shahin Shahrampour. 2545-2555 [doi]
- Layered Sampling for Robust Optimization ProblemsHu Ding, Zixiu Wang. 2556-2566 [doi]
- Growing Adaptive Multi-hyperplane MachinesNemanja Djuric, Zhuang Wang, Slobodan Vucetic. 2567-2576 [doi]
- Inexact Tensor Methods with Dynamic AccuraciesNikita Doikov, Yurii E. Nesterov. 2577-2586 [doi]
- Provable Smoothness Guarantees for Black-Box Variational InferenceJustin Domke. 2587-2596 [doi]
- Optimal Differential Privacy Composition for Exponential MechanismsJinshuo Dong, David Durfee, Ryan Rogers 0002. 2597-2606 [doi]
- Multinomial Logit Bandit with Low Switching CostKefan Dong, Yingkai Li, Qin Zhang, Yuan Zhou 0007. 2607-2615 [doi]
- Towards Adaptive Residual Network Training: A Neural-ODE PerspectiveChengyu Dong, Liyuan Liu, Zichao Li, Jingbo Shang. 2616-2626 [doi]
- On the Expressivity of Neural Networks for Deep Reinforcement LearningKefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma. 2627-2637 [doi]
- Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical SystemsZhe Dong, Bryan A. Seybold, Kevin Murphy 0002, Hung H. Bui. 2638-2647 [doi]
- Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and AlgorithmsChaosheng Dong, Bo Zeng. 2648-2657 [doi]
- The Complexity of Finding Stationary Points with Stochastic Gradient DescentYoel Drori, Ohad Shamir. 2658-2667 [doi]
- Optimal Non-parametric Learning in Repeated Contextual Auctions with Strategic BuyerAlexey Drutsa. 2668-2677 [doi]
- Reserve Pricing in Repeated Second-Price Auctions with Strategic BiddersAlexey Drutsa. 2678-2689 [doi]
- NGBoost: Natural Gradient Boosting for Probabilistic PredictionTony Duan, Avati Anand, Daisy Yi Ding, Khanh K. Thai, Sanjay Basu, Andrew Y. Ng, Alejandro Schuler. 2690-2700 [doi]
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- Online Bayesian Moment Matching based SAT Solver HeuristicsHaonan Duan, Saeed Nejati, George Trimponias, Pascal Poupart, Vijay Ganesh. 2710-2719 [doi]
- Familywise Error Rate Control by Interactive UnmaskingBoyan Duan, Aaditya Ramdas, Larry A. Wasserman. 2720-2729 [doi]
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- DROCC: Deep Robust One-Class ClassificationSachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain 0002. 3711-3721 [doi]
- Scalable Gaussian Process Separation for Kernels with a Non-Stationary PhaseJan Graßhoff, Alexandra Jankowski, Philipp Rostalski. 3722-3731 [doi]
- Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without SamplingWill Grathwohl, Kuan-Chieh Wang, Jörn-Henrik Jacobsen, David Duvenaud, Richard S. Zemel. 3732-3747 [doi]
- On the Iteration Complexity of Hypergradient ComputationRiccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo. 3748-3758 [doi]
- Robust Learning with the {HDaniel Greenfeld, Uri Shalit. 3759-3768 [doi]
- {MJean-Bastien grill, Florent Altché, Yunhao Tang, Thomas Hubert, Michal Valko, Ioannis Antonoglou, Remi Munos. 3769-3778 [doi]
- Near-Tight Margin-Based Generalization Bounds for Support Vector MachinesAllan Grønlund, Lior Kamma, Kasper Green Larsen. 3779-3788 [doi]
- Implicit Geometric Regularization for Learning ShapesAmos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, Yaron Lipman. 3789-3799 [doi]
- Improving the Gating Mechanism of Recurrent Neural NetworksAlbert Gu, Çaglar Gülçehre, Thomas Paine, Matt Hoffman 0001, Razvan Pascanu. 3800-3809 [doi]
- Recurrent Hierarchical Topic-Guided {RNNDandan Guo, Bo Chen 0001, Ruiying Lu, Mingyuan Zhou. 3810-3821 [doi]
- Breaking the Curse of Space Explosion: Towards Efficient {NASYong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen 0011, JunZhou Huang, Mingkui Tan. 3822-3831 [doi]
- Certified Data Removal from Machine Learning ModelsChuan Guo, Tom Goldstein, Awni Y. Hannun, Laurens van der Maaten. 3832-3842 [doi]
- {LTFJiaxian Guo, Mingming Gong, Tongliang Liu, Kun Zhang 0001, Dacheng Tao. 3843-3853 [doi]
- Learning to Branch for Multi-Task LearningPengsheng Guo, Chen-Yu Lee, Daniel Ulbricht. 3854-3863 [doi]
- Communication-Efficient Distributed Stochastic {AUCZhishuai Guo, Mingrui Liu, Zhuoning Yuan, Li Shen, Wei Liu, Tianbao Yang. 3864-3874 [doi]
- Bootstrap Latent-Predictive Representations for Multitask Reinforcement LearningZhaohan Daniel Guo, Bernardo Ávila Pires, Bilal Piot, Jean-Bastien grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar. 3875-3886 [doi]
- Accelerating Large-Scale Inference with Anisotropic Vector QuantizationRuiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar. 3887-3896 [doi]
- Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled DataLan-Zhe Guo, Zhenyu Zhang, Yuan Jiang, Yu-Feng Li, Zhi-Hua Zhou. 3897-3906 [doi]
- Neural Topic Modeling with Continual Lifelong LearningPankaj Gupta, Yatin Chaudhary, Thomas A. Runkler, Hinrich Schütze. 3907-3917 [doi]
- Multidimensional Shape ConstraintsMaya R. Gupta, Erez Louidor, Oleksandr Mangylov, Nobu Morioka, Taman Narayan, Sen Zhao. 3918-3928 [doi]
- Retrieval Augmented Language Model Pre-TrainingKelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, Ming-Wei Chang. 3929-3938 [doi]
- Streaming Submodular Maximization under a k-Set System ConstraintRan Haba, Ehsan Kazemi 0001, Moran Feldman, Amin Karbasi. 3939-3949 [doi]
- Let's Agree to Agree: Neural Networks Share Classification Order on Real DatasetsGuy Hacohen, Leshem Choshen, Daphna Weinshall. 3950-3960 [doi]
- Optimal approximation for unconstrained non-submodular minimizationMarwa El Halabi, Stefanie Jegelka. 3961-3972 [doi]
- {FJenny Hamer, Mehryar Mohri, Ananda Theertha Suresh. 3973-3983 [doi]
- Polynomial Tensor Sketch for Element-wise Function of Low-Rank MatrixInsu Han, Haim Avron, Jinwoo Shin. 3984-3993 [doi]
- {DRWRZhizhong Han, Chao Chen, Yu-Shen Liu, Matthias Zwicker. 3994-4005 [doi]
- {SIGUABo Han 0003, Gang Niu 0001, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama. 4006-4016 [doi]
- Training Binary Neural Networks through Learning with Noisy SupervisionKai Han, Yunhe Wang, Yixing Xu, Chunjing Xu, Enhua Wu, Chang Xu. 4017-4026 [doi]
- Stochastic Subspace Cubic {NFilip Hanzely, Nikita Doikov, Yurii E. Nesterov, Peter Richtárik. 4027-4038 [doi]
- Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum ProblemsFilip Hanzely, Dmitry Kovalev, Peter Richtárik. 4039-4048 [doi]
- Data Amplification: Instance-Optimal Property EstimationYi Hao, Alon Orlitsky. 4049-4059 [doi]
- Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential AdvertisingXiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, Han Li, Jian Xu, Kun Gai. 4060-4070 [doi]
- Improving generalization by controlling label-noise information in neural network weightsHrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan. 4071-4081 [doi]
- A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural CircuitsRamin M. Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu. 4082-4093 [doi]
- {BArman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan 0001, Xiaoning Qian. 4094-4104 [doi]
- {CLeonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, Josh Merel. 4105-4115 [doi]
- Contrastive Multi-View Representation Learning on GraphsKaveh Hassani, Amir Hosein Khas Ahmadi. 4116-4126 [doi]
- Nested Subspace Arrangement for Representation of Relational DataNozomi Hata, Shizuo Kaji, Akihiro Yoshida, Katsuki Fujisawa. 4127-4137 [doi]
- The Tree Ensemble Layer: Differentiability meets Conditional ComputationHussein Hazimeh 0001, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder. 4138-4148 [doi]
- Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximationReinhard Heckel, Mahdi Soltanolkotabi. 4149-4158 [doi]
- Hierarchically Decoupled Imitation For Morphological TransferDonald J. Hejna III, Lerrel Pinto, Pieter Abbeel. 4159-4171 [doi]
- Gradient-free Online Learning in Continuous Games with Delayed RewardsAmélie Héliou, Panayotis Mertikopoulos, Zhengyuan Zhou. 4172-4181 [doi]
- Data-Efficient Image Recognition with Contrastive Predictive CodingOlivier J. Hénaff. 4182-4192 [doi]
- Minimax Rate for Learning From Pairwise Comparisons in the {BTLJulien M. Hendrickx, Alex Olshevsky, Venkatesh Saligrama. 4193-4202 [doi]
- Statistically Preconditioned Accelerated Gradient Method for Distributed OptimizationHadrien Hendrikx, Lin Xiao, Sébastien Bubeck, Francis R. Bach, Laurent Massoulié. 4203-4227 [doi]
- Cost-Effective Interactive Attention Learning with Neural Attention ProcessesJay Heo, Junhyeon Park, Hyewon Jeong, Kwang joon Kim, Juho Lee, Eunho Yang, Sung Ju Hwang. 4228-4238 [doi]
- Likelihood-free {MCMCJoeri Hermans, Volodimir Begy, Gilles Louppe. 4239-4248 [doi]
- Towards Non-Parametric Drift Detection via Dynamic Adapting Window Independence Drift Detection ({DAWIDDFabian Hinder, André Artelt, Barbara Hammer. 4249-4259 [doi]
- Optimization and Analysis of the p{AGaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain. 4260-4270 [doi]
- Optimizing Dynamic Structures with {BMinh Hoang, Carleton Kingsford. 4271-4281 [doi]
- Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model FusionTrong Nghia Hoang, Thanh Lam, Bryan Kian Hsiang Low, Patrick Jaillet. 4282-4292 [doi]
- Parameterized Rate-Distortion Stochastic EncoderQuan Hoang, Trung Le, Dinh Phung. 4293-4303 [doi]
- Topologically Densified DistributionsChristoph D. Hofer, Florian Graf, Marc Niethammer, Roland Kwitt. 4304-4313 [doi]
- Graph Filtration LearningChristoph D. Hofer, Florian Graf, Bastian Rieck, Marc Niethammer, Roland Kwitt. 4314-4323 [doi]
- Black-Box Variational Inference as a Parametric Approximation to {LMatthew D. Hoffman, Yian Ma. 4324-4341 [doi]
- Learning Mixtures of Graphs from Epidemic CascadesJessica Hoffmann, Soumya Basu 0001, Surbhi Goel, Constantine Caramanis. 4342-4352 [doi]
- Set Functions for Time SeriesMax Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten M. Borgwardt. 4353-4363 [doi]
- Lifted Disjoint Paths with Application in Multiple Object TrackingAndrea Hornáková, Roberto Henschel, Bodo Rosenhahn, Paul Swoboda. 4364-4375 [doi]
- Infinite attention: {NNGPJiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein, Roman Novak. 4376-4386 [doi]
- The Non-{IIDKevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip B. Gibbons. 4387-4398 [doi]
- "{OHengyuan Hu, Adam Lerer, Alex Peysakhovich, Jakob N. Foerster. 4399-4410 [doi]
- {XTREMEJunjie Hu, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan Firat, Melvin Johnson. 4411-4421 [doi]
- Momentum-Based Policy Gradient MethodsFeihu Huang, Shangqian Gao, Jian Pei, Heng Huang. 4422-4433 [doi]
- From Importance Sampling to Doubly Robust Policy GradientJiawei Huang, Nan Jiang. 4434-4443 [doi]
- Evaluating Lossy Compression Rates of Deep Generative ModelsSicong Huang, Alireza Makhzani, Yanshuai Cao, Roger B. Grosse. 4444-4454 [doi]
- One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic ControlWenlong Huang, Igor Mordatch, Deepak Pathak. 4455-4464 [doi]
- Communication-Efficient Distributed {PCALong-Kai Huang, Sinno Jialin Pan. 4465-4474 [doi]
- Improving Transformer Optimization Through Better InitializationXiao Shi Huang, Felipe Pérez, Jimmy Ba, Maksims Volkovs. 4475-4483 [doi]
- More Information Supervised Probabilistic Deep Face Embedding LearningYing Huang, Shangfeng Qiu, Wenwei Zhang, Xianghui Luo, Jinzhuo Wang. 4484-4494 [doi]
- Generating Programmatic Referring Expressions via Program SynthesisJiani Huang, Calvin Smith, Osbert Bastani, Rishabh Singh, Aws Albarghouthi, Mayur Naik. 4495-4506 [doi]
- {IYangsibo Huang, Zhao Song 0002, Kai Li, Sanjeev Arora. 4507-4518 [doi]
- Accelerated Stochastic Gradient-free and Projection-free MethodsFeihu Huang, Lue Tao, Songcan Chen. 4519-4530 [doi]
- Deep Graph Random Process for Relational-Thinking-Based Speech RecognitionHengguan Huang, Fuzhao Xue, Hao Wang, Ye Wang. 4531-4541 [doi]
- Dynamics of Deep Neural Networks and Neural Tangent HierarchyJiaoyang Huang, Horng-Tzer Yau. 4542-4551 [doi]
- Curvature-corrected learning dynamics in deep neural networksDongsung Huh. 4552-4560 [doi]
- Multigrid Neural MemoryTri Huynh, Michael Maire, Matthew R. Walter. 4561-4571 [doi]
- Meta-Learning with Shared Amortized Variational InferenceEkaterina Iakovleva, Jakob Verbeek, Karteek Alahari. 4572-4582 [doi]
- Linear Lower Bounds and Conditioning of Differentiable GamesAdam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas. 4583-4593 [doi]
- Fast Deterministic {CURYasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima. 4594-4603 [doi]
- Do We Need Zero Training Loss After Achieving Zero Training Error?Takashi Ishida, Ikko Yamane, Tomoya Sakai, Gang Niu 0001, Masashi Sugiyama. 4604-4614 [doi]
- Semi-Supervised Learning with Normalizing FlowsPavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Gordon Wilson. 4615-4630 [doi]
- Implicit Regularization of Random Feature ModelsArthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel. 4631-4640 [doi]
- Correlation Clustering with Asymmetric Classification ErrorsJafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev. 4641-4650 [doi]
- Optimal Robust Learning of Discrete Distributions from BatchesAyush Jain, Alon Orlitsky. 4651-4660 [doi]
- Generalization to New Actions in Reinforcement LearningAyush Jain, Andrew Szot, Joseph J. Lim. 4661-4672 [doi]
- Tails of {LPriyank Jaini, Ivan Kobyzev, Yaoliang Yu, Marcus Brubaker. 4673-4681 [doi]
- Learning Portable Representations for High-Level PlanningSteven James, Benjamin Rosman, George Konidaris 0001. 4682-4691 [doi]
- Debiased {SHicham Janati, Marco Cuturi, Alexandre Gramfort. 4692-4701 [doi]
- Parametric {GMartin Jankowiak, Geoff Pleiss, Jacob R. Gardner. 4702-4712 [doi]
- Inverse Active Sensing: Modeling and Understanding Timely Decision-MakingDaniel Jarrett, Mihaela van der Schaar. 4713-4723 [doi]
- Source Separation with Deep Generative PriorsVivek Jayaram, John Thickstun. 4724-4735 [doi]
- Extra-gradient with player sampling for faster convergence in n-player gamesSamy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna. 4736-4745 [doi]
- T-{GDHyeonseong Jeon, Youngoh Bang, Junyaup Kim, Simon S. Woo. 4746-4761 [doi]
- History-Gradient Aided Batch Size Adaptation for Variance Reduced AlgorithmsKaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin Liang. 4762-4772 [doi]
- Information-Theoretic Local Minima Characterization and RegularizationZhiwei Jia, Hao Su 0001. 4773-4783 [doi]
- Optimizing Black-box Metrics with Adaptive SurrogatesQijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya Gupta. 4784-4793 [doi]
- {BINOCULARSShali Jiang 0001, Henry Chai, Javier Gonzalez, Roman Garnett. 4794-4803 [doi]
- Beyond Synthetic Noise: Deep Learning on Controlled Noisy LabelsLu Jiang, Di Huang, Mason Liu, Weilong Yang. 4804-4815 [doi]
- Implicit Class-Conditioned Domain Alignment for Unsupervised Domain AdaptationXiang Jiang 0001, Qicheng Lao, Stan Matwin, Mohammad Havaei. 4816-4827 [doi]
- Associative Memory in Iterated Overparameterized Sigmoid AutoencodersYibo Jiang, Cengiz Pehlevan. 4828-4838 [doi]
- Hierarchical Generation of Molecular Graphs using Structural MotifsWengong Jin, Regina Barzilay, Tommi S. Jaakkola. 4839-4848 [doi]
- Multi-Objective Molecule Generation using Interpretable SubstructuresWengong Jin, Regina Barzilay, Tommi Jaakkola. 4849-4859 [doi]
- Learning Adversarial {MChi Jin, Tiancheng Jin, Haipeng Luo, Suvrit Sra, Tiancheng Yu. 4860-4869 [doi]
- Reward-Free Exploration for Reinforcement LearningChi Jin, Akshay Krishnamurthy, Max Simchowitz, Tiancheng Yu. 4870-4879 [doi]
- What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?Chi Jin, Praneeth Netrapalli, Michael I. Jordan. 4880-4889 [doi]
- Efficiently Solving {MDPYujia Jin, Aaron Sidford. 4890-4900 [doi]
- Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising ModelYing Jin, Zhaoran Wang, Junwei Lu. 4901-4910 [doi]
- {ATyler B. Johnson, Pulkit Agrawal, Haijie Gu, Carlos Guestrin. 4911-4920 [doi]
- Guided Learning of Nonconvex Models through Successive Functional Gradient OptimizationRie Johnson, Tong Zhang 0001. 4921-4930 [doi]
- On Relativistic f-DivergencesAlexia Jolicoeur-Martineau. 4931-4939 [doi]
- Fair k-Centers via Maximum MatchingMatthew Jones, Huy Nguyen, Thy Nguyen. 4940-4949 [doi]
- Being {BTaejong Joo, Uijung Chung, Min-Gwan Seo. 4950-4961 [doi]
- Evaluating the Performance of Reinforcement Learning AlgorithmsScott M. Jordan, Yash Chandak, Daniel Cohen, Mengxue Zhang, Philip S. Thomas. 4962-4973 [doi]
- Stochastic Differential Equations with Variational Wishart DiffusionsMartin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni. 4974-4983 [doi]
- A simpler approach to accelerated optimization: iterative averaging meets optimismPooria Joulani, Anant Raj, András György, Csaba Szepesvári. 4984-4993 [doi]
- Sets ClusteringIbrahim Jubran, Murad Tukan, Alaa Maalouf, Dan Feldman. 4994-5005 [doi]
- Distribution Augmentation for Generative ModelingHeewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever. 5006-5019 [doi]
- Sub-Goal Trees a Framework for Goal-Based Reinforcement LearningTom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar. 5020-5030 [doi]
- Partial Trace Regression and Low-Rank Kraus DecompositionHachem Kadri, Stéphane Ayache, Riikka Huusari, Alain Rakotomamonjy, Liva Ralaivola. 5031-5041 [doi]
- Strategyproof Mean Estimation from Multiple-Choice QuestionsAnson Kahng, Gregory Kehne, Ariel D. Procaccia. 5042-5052 [doi]
- Variational Autoencoders with {RDimitrios Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg. 5053-5066 [doi]
- {DNathan Kallus. 5067-5077 [doi]
- Double Reinforcement Learning for Efficient and Robust Off-Policy EvaluationNathan Kallus, Masatoshi Uehara. 5078-5088 [doi]
- Statistically Efficient Off-Policy Policy GradientsNathan Kallus, Masatoshi Uehara. 5089-5100 [doi]
- On the Power of Compressed Sensing with Generative ModelsAkshay Kamath, Eric Price, Sushrut Karmalkar. 5101-5109 [doi]
- Learning and Evaluating Contextual Embedding of Source CodeAditya Kanade, Petros Maniatis, Gogul Balakrishnan, Kensen Shi. 5110-5121 [doi]
- Operation-Aware Soft Channel Pruning using Differentiable MasksMinsoo Kang, Bohyung Han. 5122-5131 [doi]
- {SCAFFOLDSai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh. 5132-5143 [doi]
- Non-autoregressive Machine Translation with Disentangled Context TransformerJungo Kasai, James Cross, Marjan Ghazvininejad, Jiatao Gu. 5144-5155 [doi]
- Transformers are {RNNAngelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas 0002, François Fleuret. 5156-5165 [doi]
- Rate-distortion optimization guided autoencoder for isometric embedding in {EKeizo Kato, Jing Zhou, Tomotake Sasaki, Akira Nakagawa. 5166-5176 [doi]
- Efficient Non-conjugate {GStephen L. Keeley, David L. Zoltowski, Yiyi Yu, Spencer L. Smith, Jonathan W. Pillow. 5177-5186 [doi]
- Quantum Expectation-Maximization for {GIordanis Kerenidis, Alessandro Luongo, Anupam Prakash. 5187-5197 [doi]
- Differentiable Likelihoods for Fast Inversion of '{LHans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Tiemann, Philipp Hennig. 5198-5208 [doi]
- Feature Noise Induces Loss Discrepancy Across GroupsFereshte Khani, Percy Liang. 5209-5219 [doi]
- Entropy Minimization In Emergent LanguagesEugene Kharitonov, Rahma Chaabouni, Diane Bouchacourt, Marco Baroni. 5220-5230 [doi]
- Private Outsourced {BDmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low. 5231-5242 [doi]
- What can I do here? {AKhimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, David Abel, Doina Precup. 5243-5253 [doi]
- Uniform Convergence of Rank-weighted LearningJustin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar. 5254-5263 [doi]
- {FACTJoon Sik Kim, Jiahao Chen, Ameet Talwalkar. 5264-5274 [doi]
- Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal MixupJang-Hyun Kim, Wonho Choo, Hyun Oh Song. 5275-5285 [doi]
- Domain Adaptive Imitation LearningKuno Kim, Yihong Gu, Jiaming Song, Shengjia Zhao, Stefano Ermon. 5286-5295 [doi]
- Variational Inference for Sequential Data with Future Likelihood EstimatesGeon-hyeong Kim, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim. 5296-5305 [doi]
- Active World Model Learning with Progress CuriosityKuno Kim, Megumi Sano, Julian De Freitas, Nick Haber, Daniel Yamins. 5306-5315 [doi]
- {BSteven Kleinegesse, Michael U. Gutmann. 5316-5326 [doi]
- Optimal Continual Learning has Perfect Memory and is {NPJeremias Knoblauch, Hisham Husain, Tom Diethe. 5327-5337 [doi]
- Concept Bottleneck ModelsPang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang. 5338-5348 [doi]
- Learning Similarity Metrics for Numerical SimulationsGeorg Kohl, Kiwon Um, Nils Thuerey. 5349-5360 [doi]
- Equivariant Flows: Exact Likelihood Generative Learning for Symmetric DensitiesJonas Köhler, Leon Klein, Frank Noé. 5361-5370 [doi]
- Online Learning for Active Cache SynchronizationAndrey Kolobov, Sébastien Bubeck, Julian Zimmert. 5371-5380 [doi]
- A Unified Theory of Decentralized {SGDAnastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian U. Stich. 5381-5393 [doi]
- Meta-learning for Mixed Linear RegressionWeihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh. 5394-5404 [doi]
- {SDELingkai Kong, Jimeng Sun, Chao Zhang. 5405-5415 [doi]
- On the Sample Complexity of Adversarial Multi-Source {PACNikola Konstantinov, Elias Frantar, Dan Alistarh, Christoph Lampert. 5416-5425 [doi]
- Asynchronous Coagent NetworksJames Kostas, Chris Nota, Philip Thomas. 5426-5435 [doi]
- Being Bayesian, Even Just a Bit, Fixes Overconfidence in {RAgustinus Kristiadi, Matthias Hein 0001, Philipp Hennig. 5436-5446 [doi]
- A Sequential Self Teaching Approach for Improving Generalization in Sound Event RecognitionAnurag Kumar, Vamsi K. Ithapu. 5447-5457 [doi]
- Curse of Dimensionality on Randomized Smoothing for Certifiable RobustnessAounon Kumar, Alexander Levine 0001, Tom Goldstein, Soheil Feizi. 5458-5467 [doi]
- Understanding Self-Training for Gradual Domain AdaptationAnanya Kumar, Tengyu Ma, Percy Liang. 5468-5479 [doi]
- On Implicit Regularization in $β$-{VAEAbhishek Kumar, Ben Poole. 5480-5490 [doi]
- Problems with Shapley-value-based explanations as feature importance measuresI. Elizabeth Kumar, Suresh Venkatasubramanian, Carlos Scheidegger, Sorelle A. Friedler. 5491-5500 [doi]
- Efficient Identification in Linear Structural Causal Models with Auxiliary CutsetsDaniel Kumor, Carlos Cinelli, Elias Bareinboim. 5501-5510 [doi]
- Two Routes to Scalable Credit Assignment without Weight SymmetryDaniel Kunin, Aran Nayebi, Javier Sagastuy-Breña, Surya Ganguli, Jonathan M. Bloom, Daniel Yamins. 5511-5521 [doi]
- Online Dense Subgraph Discovery via Blurred-Graph FeedbackYuko Kuroki, Atsushi Miyauchi 0001, Junya Honda, Masashi Sugiyama. 5522-5532 [doi]
- Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural NetworksMark Kurtz, Justin Kopinsky, Rati Gelashvili, Alexander Matveev, John Carr, Michael Goin, William M. Leiserson, Sage Moore, Nir Shavit, Dan Alistarh. 5533-5543 [doi]
- Soft Threshold Weight Reparameterization for Learnable SparsityAditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain 0002, Sham M. Kakade, Ali Farhadi. 5544-5555 [doi]
- Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile CriticsArsenii Kuznetsov, Pavel Shvechikov, Alexander Grishin, Dmitry P. Vetrov. 5556-5566 [doi]
- Principled learning method for {WYongchan Kwon, Wonyoung Kim, Joong-Ho Won, Myunghee Cho Paik. 5567-5576 [doi]
- Concentration bounds for {CVPrashanth L. A., Krishna P. Jagannathan, Ravi Kumar Kolla. 5577-5586 [doi]
- Optimal Randomized First-Order Methods for Least-Squares ProblemsJonathan Lacotte, Mert Pilanci. 5587-5597 [doi]
- Duality in {RKHSPierre Laforgue, Alex Lambert, Luc Brogat-Motte, Florence d'Alché-Buc. 5598-5607 [doi]
- Recht-Re Noncommutative Arithmetic-Geometric Mean Conjecture is FalseZehua Lai, Lek-Heng Lim. 5608-5617 [doi]
- Bidirectional Model-based Policy OptimizationHang Lai, Jian Shen 0003, Weinan Zhang 0001, Yong Yu 0001. 5618-5627 [doi]
- Robust and Stable Black Box ExplanationsHimabindu Lakkaraju, Nino Arsov, Osbert Bastani. 5628-5638 [doi]
- {CURLMichael Laskin, Aravind Srinivas, Pieter Abbeel. 5639-5650 [doi]
- Efficient Proximal Mapping of the 1-path-norm of Shallow NetworksFabian Latorre Gómez, Paul Rolland, Nadav Hallak, Volkan Cevher. 5651-5661 [doi]
- Learning with Good Feature Representations in Bandits and in {RLTor Lattimore, Csaba Szepesvári, Gellért Weisz. 5662-5670 [doi]
- Inertial Block Proximal Methods for Non-Convex Non-Smooth OptimizationHien Le, Nicolas Gillis, Panagiotis Patrinos. 5671-5681 [doi]
- Self-Attentive Associative MemoryHung Le, Truyen Tran 0001, Svetha Venkatesh. 5682-5691 [doi]
- Causal Effect Identifiability under Partial-ObservabilitySanghack Lee, Elias Bareinboim. 5692-5701 [doi]
- Estimating Model Uncertainty of Neural Networks in Sparse Information FormJongseok Lee, Matthias Humt, Jianxiang Feng, Rudolph Triebel. 5702-5713 [doi]
- Self-supervised Label Augmentation via Input TransformationsHankook Lee, Sung Ju Hwang, Jinwoo Shin. 5714-5724 [doi]
- Batch Reinforcement Learning with Hyperparameter GradientsByung Jun Lee, Jongmin Lee, Peter Vrancx, DongHo Kim, Kee-Eung Kim. 5725-5735 [doi]
- Accelerated Message Passing for Entropy-Regularized {MAPJonathan N. Lee, Aldo Pacchiano, Peter L. Bartlett, Michael I. Jordan. 5736-5746 [doi]
- Learning Compound Tasks without Task-specific Knowledge via Imitation and Self-supervised LearningSang Hyun Lee, Seung-Woo Seo. 5747-5756 [doi]
- Context-aware Dynamics Model for Generalization in Model-Based Reinforcement LearningKimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, Jinwoo Shin. 5757-5766 [doi]
- Temporal Phenotyping using Deep Predictive Clustering of Disease ProgressionChangHee Lee, Mihaela van der Schaar. 5767-5777 [doi]
- Tensor denoising and completion based on ordinal observationsChanwoo Lee, Miaoyan Wang. 5778-5788 [doi]
- Analytic Marching: An Analytic Meshing Solution from Deep Implicit Surface NetworksJiabao Lei, Kui Jia. 5789-5798 [doi]
- {SGDQi Lei, Jason D. Lee, Alex Dimakis, Constantinos Daskalakis. 5799-5808 [doi]
- Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient DescentYunwen Lei, Yiming Ying. 5809-5819 [doi]
- Learning Quadratic Games on NetworksYan Leng, Xiaowen Dong, Junfeng Wu, Alex Pentland. 5820-5830 [doi]
- {ACFYang Li, Shoaib Akbar, Junier Oliva. 5831-5841 [doi]
- Manifold Identification for Ultimately Communication-Efficient Distributed OptimizationYu-Sheng Li, Wei-Lin Chiang, Ching-Pei Lee. 5842-5852 [doi]
- Neural Architecture Search in A Proxy Validation Loss LandscapeYanxi Li, Minjing Dong, Yunhe Wang, Chang Xu. 5853-5862 [doi]
- {PENNIShiyu Li, Edward Hanson, Hai Li, Yiran Chen. 5863-5873 [doi]
- Implicit {EMingjie Li, Lingshen He, Zhouchen Lin. 5874-5883 [doi]
- Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic ReasoningQing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song Chun Zhu. 5884-5894 [doi]
- Acceleration for Compressed Gradient Descent in Distributed and Federated OptimizationZhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik. 5895-5904 [doi]
- On the Relation between Quality-Diversity Evaluation and Distribution-Fitting Goal in Text GenerationJianing Li, Yanyan Lan, Jiafeng Guo, Xueqi Cheng. 5905-5915 [doi]
- Latent Space Factorisation and Manipulation via Matrix Subspace ProjectionXiao Li, Chenghua Lin, Ruizhe Li, Chaozheng Wang, Frank Guerin. 5916-5926 [doi]
- Visual Grounding of Learned Physical ModelsYunzhu Li, Toru Lin, Kexin Yi, Daniel Bear, Daniel Yamins, Jiajun Wu 0001, Joshua B. Tenenbaum, Antonio Torralba 0001. 5927-5936 [doi]
- Learning from Irregularly-Sampled Time Series: A Missing Data PerspectiveSteven Cheng-Xian Li, Benjamin M. Marlin. 5937-5946 [doi]
- Evolutionary Topology Search for Tensor Network DecompositionChao Li, Zhun Sun. 5947-5957 [doi]
- Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of TransformersZhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joey Gonzalez. 5958-5968 [doi]
- Almost Tune-Free Variance ReductionBingcong Li, Lingda Wang, Georgios B. Giannakis. 5969-5978 [doi]
- Nearly Linear Row Sampling Algorithm for Quantile RegressionYi Li, Ruosong Wang, Lin Yang, Hanrui Zhang. 5979-5989 [doi]
- Temporal Logic Point ProcessesShuang Li 0002, Lu Wang, Ruizhi Zhang, Xiaofu Chang, Xuqin Liu, Yao Xie, Yuan Qi, Le Song. 5990-6000 [doi]
- Input-Sparsity Low Rank Approximation in Schatten NormYi Li, David P. Woodruff. 6001-6009 [doi]
- {RIFLEXingjian Li 0002, Haoyi Xiong, Haozhe An, Cheng-Zhong Xu 0001, Dejing Dou. 6010-6019 [doi]
- On a projective ensemble approach to two sample test for equality of distributionsZhimei Li, Yaowu Zhang. 6020-6027 [doi]
- Do We Really Need to Access the Source Data? {SJian Liang, Dapeng Hu, Jiashi Feng. 6028-6039 [doi]
- Variable Skipping for Autoregressive Range Density EstimationEric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Peter Chen. 6040-6049 [doi]
- Adaptive Droplet Routing in Digital Microfluidic Biochips Using Deep Reinforcement LearningTung-Che Liang, Zhanwei Zhong, Yaas Bigdeli, Tsung-Yi Ho, Krishnendu Chakrabarty, Richard B. Fair. 6050-6060 [doi]
- {ARJae Hyun Lim, Aaron C. Courville, Christopher J. Pal, Chin-Wei Huang. 6061-6071 [doi]
- Hierarchical Verification for Adversarial RobustnessCong Han Lim, Raquel Urtasun, Ersin Yumer. 6072-6082 [doi]
- On Gradient Descent Ascent for Nonconvex-Concave Minimax ProblemsTianyi Lin, Chi Jin, Michael I. Jordan. 6083-6093 [doi]
- Extrapolation for Large-batch Training in Deep LearningTao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi. 6094-6104 [doi]
- On the Theoretical Properties of the Network JackknifeQiaohui Lin, Robert Lunde, Purnamrita Sarkar. 6105-6115 [doi]
- Handling the Positive-Definite Constraint in the {BWu Lin, Mark Schmidt 0001, Mohammad Emtiyaz Khan. 6116-6126 [doi]
- {IZinan Lin 0001, Kiran Koshy Thekumparampil, Giulia C. Fanti, Sewoong Oh. 6127-6139 [doi]
- Improving Generative Imagination in Object-Centric World ModelsZhixuan Lin, Yi-Fu Wu, Skand Vishwanath Peri, Bofeng Fu, Jindong Jiang, Sungjin Ahn. 6140-6149 [doi]
- Generalized and Scalable Optimal Sparse Decision TreesJimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo I. Seltzer. 6150-6160 [doi]
- Finite-Time Last-Iterate Convergence for Multi-Agent Learning in GamesTianyi Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael I. Jordan. 6161-6171 [doi]
- Time-aware Large Kernel ConvolutionsVasileios Lioutas, Yuhong Guo. 6172-6183 [doi]
- Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance SamplingYao Liu 0009, Pierre-Luc Bacon, Emma Brunskill. 6184-6193 [doi]
- Sparse Shrunk Additive ModelsGuodong Liu, Hong Chen, Heng Huang. 6194-6204 [doi]
- Boosting Deep Neural Network Efficiency with Dual-Module InferenceLiu Liu, Lei Deng, Zhaodong Chen, Yuke Wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie. 6205-6215 [doi]
- Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative PriorsZhaoqiang Liu, Selwyn Gomes, Avtansh Tiwari, Jonathan Scarlett. 6216-6225 [doi]
- Peer Loss Functions: Learning from Noisy Labels without Knowing Noise RatesYang Liu, Hongyi Guo. 6226-6236 [doi]
- An Imitation Learning Approach for Cache ReplacementEvan Zheran Liu, Milad Hashemi, Kevin Swersky, Parthasarathy Ranganathan, Junwhan Ahn. 6237-6247 [doi]
- Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed BanditsXi Liu 0011, Ping-Chun Hsieh, Yu-Heng Hung, Anirban Bhattacharya, P. R. Kumar. 6248-6258 [doi]
- Hallucinative Topological Memory for Zero-Shot Visual PlanningKara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar. 6259-6270 [doi]
- A Chance-Constrained Generative Framework for Sequence OptimizationXianggen Liu, Qiang Liu, Sen Song, Jian Peng 0001. 6271-6281 [doi]
- Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning AttacksSijia Liu 0001, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O'Reilly. 6282-6293 [doi]
- Median Matrix Completion: from Embarrassment to OptimalityWeidong Liu, Xiaojun Mao, Raymond K. W. Wong. 6294-6304 [doi]
- A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level SingletonRisheng Liu, Pan Mu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang. 6305-6315 [doi]
- Learning Deep Kernels for Non-Parametric Two-Sample TestsFeng Liu, Wenkai Xu, Jie Lu, Guangquan Zhang 0001, Arthur Gretton, Dougal J. Sutherland. 6316-6326 [doi]
- Learning to Encode Position for Transformer with Continuous Dynamical ModelXuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh. 6327-6335 [doi]
- Finding trainable sparse networks through Neural Tangent TransferTianlin Liu, Friedemann Zenke. 6336-6347 [doi]
- Weakly-Supervised Disentanglement Without CompromisesFrancesco Locatello, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, Michaël Tschannen. 6348-6359 [doi]
- Too Relaxed to Be FairMichael Lohaus, Michael Perrot, Ulrike von Luxburg. 6360-6369 [doi]
- Stochastic {HNicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas. 6370-6381 [doi]
- Error Estimation for Sketched {SVDMiles Lopes, N. Benjamin Erichson, Michael W. Mahoney. 6382-6392 [doi]
- Differentiating through the Fr{éAaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa. 6393-6403 [doi]
- Working Memory GraphsRicky Loynd, Roland Fernandez, Asli Çelikyilmaz, Adith Swaminathan, Matthew J. Hausknecht. 6404-6414 [doi]
- Moniqua: Modulo Quantized Communication in Decentralized {SGDYucheng Lu, Christopher De Sa. 6415-6425 [doi]
- A Mean Field Analysis Of Deep {RYiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu 0001, Lexing Ying. 6426-6436 [doi]
- Countering Language Drift with Seeded Iterated LearningYuchen Lu, Soumye Singhal, Florian Strub, Aaron C. Courville, Olivier Pietquin. 6437-6447 [doi]
- Does label smoothing mitigate label noise?Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar. 6448-6458 [doi]
- Improved Communication Cost in Distributed {PSiqiang Luo. 6459-6467 [doi]
- Progressive Graph Learning for Open-Set Domain AdaptationYadan Luo, Zijian Wang, Zi Huang, Mahsa Baktashmotlagh. 6468-6478 [doi]
- Adversarial Nonnegative Matrix FactorizationLei Luo 0001, Yanfu Zhang, Heng Huang. 6479-6488 [doi]
- Learning Algebraic Multigrid Using Graph Neural NetworksIlay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh. 6489-6499 [doi]
- Progressive Identification of True Labels for Partial-Label LearningJiaqi Lv, Miao Xu, Lei Feng, Gang Niu 0001, Xin Geng, Masashi Sugiyama. 6500-6510 [doi]
- Bandits with Adversarial ScalingThodoris Lykouris, Vahab S. Mirrokni, Renato Paes Leme. 6511-6521 [doi]
- Efficient Continuous Pareto Exploration in Multi-Task LearningPingchuan Ma 0002, Tao Du, Wojciech Matusik. 6522-6531 [doi]
- Convex Representation Learning for Generalized Invariance in Semi-Inner-Product SpaceYingyi Ma, Vignesh Ganapathiraman, Yaoliang Yu, Xinhua Zhang. 6532-6542 [doi]
- Normalized Loss Functions for Deep Learning with Noisy LabelsXingjun Ma, Hanxun Huang, Yisen Wang 0001, Simone Romano 0003, Sarah M. Erfani, James Bailey 0001. 6543-6553 [doi]
- Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex ConstraintsRunchao Ma, Qihang Lin, Tianbao Yang. 6554-6564 [doi]
- Understanding the Impact of Model Incoherence on Convergence of Incremental {SGDShaocong Ma, Yi Zhou. 6565-6574 [doi]
- Adversarial Neural Pruning with Latent Vulnerability SuppressionDivyam Madaan, Jinwoo Shin, Sung Ju Hwang. 6575-6585 [doi]
- Individual Fairness for k-ClusteringSepideh Mahabadi, Ali Vakilian. 6586-6596 [doi]
- Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto OptimizationDebabrata Mahapatra, Vaibhav Rajan. 6597-6607 [doi]
- How recurrent networks implement contextual processing in sentiment analysisNiru Maheswaranathan, David Sussillo. 6608-6619 [doi]
- Anderson Acceleration of Proximal Gradient MethodsVien V. Mai, Mikael Johansson 0001. 6620-6629 [doi]
- Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex OptimizationVien V. Mai, Mikael Johansson 0001. 6630-6639 [doi]
- Adversarial Robustness Against the Union of Multiple Perturbation ModelsPratyush Maini, Eric Wong, Zico Kolter. 6640-6650 [doi]
- Evolutionary Reinforcement Learning for Sample-Efficient Multiagent CoordinationSomdeb Majumdar, Shauharda Khadka, Santiago Miret, Stephen McAleer, Kagan Tumer. 6651-6660 [doi]
- Estimation of Bounds on Potential Outcomes For Decision MakingMaggie Makar, Fredrik D. Johansson, John V. Guttag, David A. Sontag. 6661-6671 [doi]
- Optimal transport mapping via input convex neural networksAshok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason D. Lee. 6672-6681 [doi]
- Proving the Lottery Ticket Hypothesis: Pruning is All You NeedEran Malach, Gilad Yehudai, Shai Shalev-Shwartz, Ohad Shamir. 6682-6691 [doi]
- From Local {SGDGrigory Malinovskiy, Dmitry Kovalev, Elnur Gasanov, Laurent Condat, Peter Richtárik. 6692-6701 [doi]
- Adaptive Gradient Descent without DescentYura Malitsky, Konstantin Mishchenko. 6702-6712 [doi]
- Emergence of Separable Manifolds in Deep Language RepresentationsJonathan Mamou, Hang Le, Miguel Del Rio, Cory Stephenson, Hanlin Tang, Yoon Kim, SueYeon Chung. 6713-6723 [doi]
- Adaptive Adversarial Multi-task Representation LearningYuren Mao, Weiwei Liu 0003, Xuemin Lin 0001. 6724-6733 [doi]
- On Learning Sets of Symmetric ElementsHaggai Maron, Or Litany, Gal Chechik, Ethan Fetaya. 6734-6744 [doi]
- Stochastically Dominant Distributional Reinforcement LearningJohn D. Martin, Michal Lyskawinski, Xiaohu Li, Brendan J. Englot. 6745-6754 [doi]
- Minimax Pareto Fairness: A Multi Objective PerspectiveNatalia Martínez, Martin Bertrán, Guillermo Sapiro. 6755-6764 [doi]
- Predictive Multiplicity in ClassificationCharles T. Marx, Flávio P. Calmon, Berk Ustun. 6765-6774 [doi]
- Adding seemingly uninformative labels helps in low data regimesChristos Matsoukas, Albert Bou I Hernandez, Yue Liu, Karin Dembrower, Gisele Miranda, Emir Konuk, Johan Fredin Haslum, Athanasios Zouzos, Peter Lindholm, Fredrik Strand, Kevin Smith 0001. 6775-6784 [doi]
- Fast and Consistent Learning of Hidden {MRobert Mattila, Cristian R. Rojas, Eric Moulines, Vikram Krishnamurthy, Bo Wahlberg. 6785-6796 [doi]
- On Approximate Thompson Sampling with {LEric Mazumdar, Aldo Pacchiano, Yi-An Ma, Michael I. Jordan, Peter L. Bartlett. 6797-6807 [doi]
- Neural Datalog Through Time: Informed Temporal Modeling via Logical SpecificationHongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner. 6808-6819 [doi]
- On the Global Convergence Rates of Softmax Policy Gradient MethodsJincheng Mei, Chenjun Xiao, Csaba Szepesvári, Dale Schuurmans. 6820-6829 [doi]
- Scalable Identification of Partially Observed Systems with Certainty-Equivalent {EMKunal Menda, Jean de Becdelièvre, Jayesh K. Gupta, Ilan Kroo, Mykel J. Kochenderfer, Zachary Manchester. 6830-6840 [doi]
- Randomized Block-Diagonal Preconditioning for Parallel LearningCelestine Mendler-Dünner, Aurélien Lucchi. 6841-6851 [doi]
- Training Binary Neural Networks using the {BXiangming Meng, Roman Bachmann, Mohammad Emtiyaz Khan. 6852-6861 [doi]
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- The Role of Regularization in Classification of High-dimensional Noisy {GFrancesca Mignacco, Florent Krzakala, Yue Lu, Pierfrancesco Urbani, Lenka Zdeborová. 6874-6883 [doi]
- Projective Preferential {BPetrus Mikkola, Milica Todorovic, Jari Järvi, Patrick Rinke, Samuel Kaski. 6884-6892 [doi]
- {VZoltán Ádám Milacski, Barnabás Póczos, András Lörincz. 6893-6904 [doi]
- The Effect of Natural Distribution Shift on Question Answering ModelsJohn Miller, Karl Krauth, Benjamin Recht, Ludwig Schmidt. 6905-6916 [doi]
- Strategic Classification is Causal Modeling in DisguiseJohn Miller, Smitha Milli, Moritz Hardt. 6917-6926 [doi]
- Automatic Shortcut Removal for Self-Supervised Representation LearningMatthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen. 6927-6937 [doi]
- Learning Reasoning Strategies in End-to-End Differentiable ProvingPasquale Minervini, Sebastian Riedel 0001, Pontus Stenetorp, Edward Grefenstette, Tim Rocktäschel. 6938-6949 [doi]
- Coresets for Data-efficient Training of Machine Learning ModelsBaharan Mirzasoleiman, Jeff A. Bilmes, Jure Leskovec. 6950-6960 [doi]
- Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement LearningDipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford 0001. 6961-6971 [doi]
- Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over ModulesSarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio. 6972-6986 [doi]
- Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching ApproachMartin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard S. Zemel, Craig Boutilier. 6987-6998 [doi]
- Transformation of {RZahra Monfared, Daniel Durstewitz. 6999-7009 [doi]
- Efficiently Learning Adversarially Robust Halfspaces with NoiseOmar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro. 7010-7021 [doi]
- An end-to-end approach for the verification problem: learning the right distanceJoão Monteiro, Isabela Albuquerque, Md. Jahangir Alam, R. Devon Hjelm, Tiago H. Falk. 7022-7033 [doi]
- Confidence-Aware Learning for Deep Neural NetworksJooyoung Moon, Jihyo Kim, Younghak Shin, Sangheum Hwang. 7034-7044 [doi]
- Topological AutoencodersMichael Moor, Max Horn, Bastian Rieck, Karsten M. Borgwardt. 7045-7054 [doi]
- Explainable k-Means and k-Medians ClusteringMichal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost. 7055-7065 [doi]
- Fair Learning with Private Demographic DataHussein Mozannar, Mesrob I. Ohannessian, Nathan Srebro. 7066-7075 [doi]
- Consistent Estimators for Learning to Defer to an ExpertHussein Mozannar, David A. Sontag. 7076-7087 [doi]
- Continuous-time Lower Bounds for Gradient-based AlgorithmsMichael Muehlebach, Michael I. Jordan. 7088-7096 [doi]
- Two Simple Ways to Learn Individual Fairness Metrics from DataDebarghya Mukherjee, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun. 7097-7107 [doi]
- Unique Properties of Flat Minima in Deep NetworksRotem Mulayoff, Tomer Michaeli. 7108-7118 [doi]
- Fast computation of {NRémi Munos, Julien Pérolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls. 7119-7129 [doi]
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- Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable GuaranteesSen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar. 7141-7152 [doi]
- Full Law Identification in Graphical Models of Missing Data: Completeness ResultsRazieh Nabi, Rohit Bhattacharya, Ilya Shpitser. 7153-7163 [doi]
- Voice Separation with an Unknown Number of Multiple SpeakersEliya Nachmani, Yossi Adi, Lior Wolf. 7164-7175 [doi]
- Reliable Fidelity and Diversity Metrics for Generative ModelsMuhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, Jaejun Yoo. 7176-7185 [doi]
- From Chaos to Order: Symmetry and Conservation Laws in Game DynamicsSai Ganesh Nagarajan, David Balduzzi, Georgios Piliouras. 7186-7196 [doi]
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- Goal-Aware Prediction: Learning to Model What MattersSuraj Nair, Silvio Savarese, Chelsea Finn. 7207-7219 [doi]
- {PCharlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter W. Battaglia. 7220-7229 [doi]
- {BIvan Nazarov, Evgeny Burnaev. 7230-7242 [doi]
- Oracle Efficient Private Non-Convex OptimizationSeth Neel, Aaron Roth 0001, Giuseppe Vietri, Steven Z. Wu. 7243-7252 [doi]
- Stochastic Frank-{WGeoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Robert Freund, Fabian Pedregosa. 7253-7262 [doi]
- In Defense of Uniform Convergence: Generalization via Derandomization with an Application to Interpolating PredictorsJeffrey Negrea, Gintare Karolina Dziugaite, Daniel Roy 0001. 7263-7272 [doi]
- Involutive {MCMCKirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry P. Vetrov. 7273-7282 [doi]
- Aggregation of Multiple KnockoffsTuan-Binh Nguyen, Jérome-Alexis Chevalier, Bertrand Thirion, Sylvain Arlot. 7283-7293 [doi]
- {LEEPCuong Nguyen, Tal Hassner, Matthias W. Seeger, Cédric Archambeau. 7294-7305 [doi]
- Graph Homomorphism ConvolutionHoang Nguyen, Takanori Maehara. 7306-7316 [doi]
- Knowing The What But Not The Where in {BVu Nguyen, Michael A. Osborne. 7317-7326 [doi]
- Robust {BViet Anh Nguyen, Nian Si, Jose H. Blanchet. 7327-7337 [doi]
- Streaming k-Submodular Maximization under Noise subject to Size ConstraintLan Nguyen, My T. Thai. 7338-7347 [doi]
- {LPVlad Niculae, André F. T. Martins. 7348-7359 [doi]
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- Supervised learning: no loss no cryRichard Nock, Aditya Krishna Menon. 7370-7380 [doi]
- Consistent Structured Prediction with Max-Min Margin {MAlex Nowak, Francis R. Bach, Alessandro Rudi. 7381-7391 [doi]
- T-Basis: a Compact Representation for Neural NetworksAnton Obukhov, Maxim V. Rakhuba, Stamatios Georgoulis, Menelaos Kanakis, Dengxin Dai, Luc Van Gool. 7392-7404 [doi]
- Eliminating the Invariance on the Loss Landscape of Linear AutoencodersReza Oftadeh, Jiayi Shen, Zhangyang Wang, Dylan A. Shell. 7405-7413 [doi]
- On the ({INaoto Ohsaka, Tatsuya Matsuoka. 7414-7423 [doi]
- Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?Kei Ota, Tomoaki Oiki, Devesh K. Jha, Toshisada Mariyama, Daniel Nikovski. 7424-7433 [doi]
- Interferometric Graph Transform: a Deep Unsupervised Graph RepresentationEdouard Oyallon. 7434-7444 [doi]
- Learning to Score Behaviors for Guided Policy OptimizationAldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Krzysztof Choromanski, Anna Choromanska, Michael I. Jordan. 7445-7454 [doi]
- Neural Clustering ProcessesAri Pakman, Yueqi Wang, Catalin Mitelut, Jin Hyung Lee, Liam Paninski. 7455-7465 [doi]
- Recovery of Sparse Signals from a Mixture of Linear SamplesSoumyabrata Pal, Arya Mazumdar. 7466-7475 [doi]
- Adversarial Mutual Information for Text GenerationBoyuan Pan, Yazheng Yang, Kaizhao Liang, Bhavya Kailkhura, Zhongming Jin, Xian-Sheng Hua 0001, Deng Cai, Bo Li. 7476-7486 [doi]
- Stabilizing Transformers for Reinforcement LearningEmilio Parisotto, H. Francis Song, Jack W. Rae, Razvan Pascanu, Çaglar Gülçehre, Siddhant M. Jayakumar, Max Jaderberg, Raphaël Lopez Kaufman, Aidan Clark, Seb Noury, Matthew Botvinick, Nicolas Heess, Raia Hadsell. 7487-7498 [doi]
- Multiresolution Tensor Learning for Efficient and Interpretable Spatial AnalysisJung Yeon Park, Kenneth Theo Carr, Stephan Zheng, Yisong Yue, Rose Yu. 7499-7509 [doi]
- Meta Variance Transfer: Learning to Augment from the OthersSeong-Jin Park, Seungju Han, Ji Won Baek, Insoo Kim, Juhwan Song, Haebeom Lee, Jae-Joon Han, Sung Ju Hwang. 7510-7520 [doi]
- Structured Policy Iteration for Linear Quadratic RegulatorYoungsuk Park, Ryan A. Rossi, Zheng Wen, Gang Wu, Handong Zhao. 7521-7531 [doi]
- Regularized Optimal Transport is Ground Cost AdversarialFrançois-Pierre Paty, Marco Cuturi. 7532-7542 [doi]
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- Learning Selection Strategies in Buchberger's AlgorithmDylan Peifer, Michael Eugene Stillman, Daniel Halpern-Leistner. 7575-7585 [doi]
- Non-Autoregressive Neural Text-to-SpeechKainan Peng, Wei Ping, Zhao Song 0001, Kexin Zhao. 7586-7598 [doi]
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- Constructive Universal High-Dimensional Distribution Generation through Deep {RDmytro Perekrestenko, Stephan Müller, Helmut Bölcskei. 7610-7619 [doi]
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- Low Bias Low Variance Gradient Estimates for Boolean Stochastic NetworksAdeel Pervez, Taco Cohen, Efstratios Gavves. 7632-7640 [doi]
- On Convergence-Diagnostic based Step Sizes for Stochastic Gradient DescentScott Pesme, Aymeric Dieuleveut, Nicolas Flammarion. 7641-7651 [doi]
- Sample Factory: Egocentric 3{DAleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav Sukhatme, Vladlen Koltun. 7652-7662 [doi]
- {IPBMarc E. Pfetsch, Sebastian Pokutta. 7663-7672 [doi]
- On Unbalanced Optimal Transport: An Analysis of {SKhiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui. 7673-7682 [doi]
- Scalable Differential Privacy with Certified Robustness in Adversarial LearningHai Phan, My T. Thai, Han Hu, Ruoming Jin, Tong Sun, Dejing Dou. 7683-7694 [doi]
- Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer NetworksMert Pilanci, Tolga Ergen. 7695-7705 [doi]
- {WWei Ping, Kainan Peng, Kexin Zhao, Zhao Song 0001. 7706-7716 [doi]
- Randomization matters How to defend against strong adversarial attacksRafael Pinot, Raphael Ettedgui, Geovani Rizk, Yann Chevaleyre, Jamal Atif. 7717-7727 [doi]
- Efficient Domain Generalization via Common-Specific Low-Rank DecompositionVihari Piratla, Praneeth Netrapalli, Sunita Sarawagi. 7728-7738 [doi]
- Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field ApproximationKonstantinos Pitas. 7739-7749 [doi]
- Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement LearningSilviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba. 7750-7761 [doi]
- Explaining Groups of Points in Low-Dimensional RepresentationsGregory Plumb, Jonathan Terhorst, Sriram Sankararaman, Ameet Talwalkar. 7762-7771 [doi]
- On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to SharpnessSebastian Pokutta, Mohit Singh, Alfredo Torrico. 7772-7782 [doi]
- Skew-Fit: State-Covering Self-Supervised Reinforcement LearningVitchyr Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, Sergey Levine. 7783-7792 [doi]
- {SSebastian Prillo, Julian Eisenschlos. 7793-7802 [doi]
- Graph-based Nearest Neighbor Search: From Practice to TheoryLiudmila Prokhorenkova, Aleksandr Shekhovtsov. 7803-7813 [doi]
- Adversarial Risk via Optimal Transport and Optimal CouplingsMuni Sreenivas Pydi, Varun Jog. 7814-7823 [doi]
- Deep Isometric Learning for Visual RecognitionHaozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik. 7824-7835 [doi]
- Unsupervised Speech Decomposition via Triple Information BottleneckKaizhi Qian, Yang Zhang, Shiyu Chang, Mark Hasegawa-Johnson, David Cox. 7836-7846 [doi]
- Scalable Differentiable Physics for Learning and ControlYi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin. 7847-7856 [doi]
- Robust One-Bit Recovery via {RShuang Qiu, Xiaohan Wei, Zhuoran Yang. 7857-7866 [doi]
- Few-shot Relation Extraction via {BMeng Qu, Tianyu Gao, Louis-Pascal A. C. Xhonneux, Jian Tang. 7867-7876 [doi]
- {DThomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta 0001, Svetha Venkatesh. 7877-7886 [doi]
- Fast and Private Submodular and k-Submodular Functions Maximization with Matroid ConstraintsAkbar Rafiey, Yuichi Yoshida. 7887-7897 [doi]
- Transparency Promotion with Model-Agnostic Linear CompetitorsHassan Rafique, Tong Wang, Qihang Lin, Arshia Singhani. 7898-7908 [doi]
- Understanding and Mitigating the Tradeoff between Robustness and AccuracyAditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang. 7909-7919 [doi]
- Fast Adaptation to New Environments via Policy-Dynamics Value FunctionsRoberta Raileanu, Max Goldstein, Arthur Szlam, Rob Fergus. 7920-7931 [doi]
- Improving Robustness of Deep-Learning-Based Image ReconstructionAnkit Raj, Yoram Bresler, Bo Li. 7932-7942 [doi]
- Multi-Precision Policy Enforced Training ({MAditya Rajagopal, Diederik Adriaan Vink, Stylianos I. Venieris, Christos-Savvas Bouganis. 7943-7952 [doi]
- A Game Theoretic Framework for Model Based Reinforcement LearningAravind Rajeswaran, Igor Mordatch, Vikash Kumar. 7953-7963 [doi]
- Closing the convergence gap of {SGDShashank Rajput, Anant Gupta, Dimitris S. Papailiopoulos. 7964-7973 [doi]
- Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement LearningAmin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu 0001, Adish Singla. 7974-7984 [doi]
- Implicit Generative Modeling for Efficient ExplorationNeale Ratzlaff, Qinxun Bai, Fuxin Li, Wei Xu. 7985-7995 [doi]
- Universal Equivariant Multilayer PerceptronsSiamak Ravanbakhsh. 7996-8006 [doi]
- {AEsteban Real, Chen Liang, David R. So, Quoc V. Le. 8007-8019 [doi]
- Learning Human Objectives by Evaluating Hypothetical BehaviorSiddharth Reddy, Anca D. Dragan, Sergey Levine, Shane Legg, Jan Leike. 8020-8029 [doi]
- Optimistic Bounds for Multi-output LearningHenry W. J. Reeve, Ata Kabán. 8030-8040 [doi]
- Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query GenerationFlorence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates. 8041-8050 [doi]
- The Sample Complexity of Best-k Items Selection from Pairwise ComparisonsWenbo Ren, Jia Liu 0002, Ness B. Shroff. 8051-8072 [doi]
- {NLuca Rendsburg, Holger Heidrich, Ulrike von Luxburg. 8073-8082 [doi]
- Normalizing Flows on Tori and SpheresDanilo Jimenez Rezende, George Papamakarios, Sébastien Racanière, Michael S. Albergo, Gurtej Kanwar, Phiala E. Shanahan, Kyle Cranmer. 8083-8092 [doi]
- Overfitting in adversarially robust deep learningLeslie Rice, Eric Wong, Zico Kolter. 8093-8104 [doi]
- Decentralised Learning with Random Features and Distributed Gradient DescentDominic Richards, Patrick Rebeschini, Lorenzo Rosasco. 8105-8115 [doi]
- Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior KnowledgeLaura Rieger, Chandan Singh, W. James Murdoch, Bin Yu. 8116-8126 [doi]
- Strength from Weakness: Fast Learning Using Weak SupervisionJoshua Robinson, Stefanie Jegelka, Suvrit Sra. 8127-8136 [doi]
- On Semi-parametric Inference for {BARTVeronika Rocková. 8137-8146 [doi]
- {FRYuji Roh, Kangwook Lee, Steven Whang, Changho Suh. 8147-8157 [doi]
- Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine LearningEsther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock. 8158-8168 [doi]
- Double-Loop Unadjusted {LPaul Rolland, Armin Eftekhari, Ali Kavis, Volkan Cevher. 8169-8177 [doi]
- Reverse-engineering deep {RDavid Rolnick, Konrad P. Kording. 8178-8187 [doi]
- Attentive Group Equivariant Convolutional NetworksDavid W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn. 8188-8199 [doi]
- Finite-Time Convergence in Continuous-Time OptimizationOrlando Romero, Mouhacine Benosman. 8200-8209 [doi]
- Near-optimal Regret Bounds for Stochastic Shortest PathAviv Rosenberg 0002, Alon Cohen, Yishay Mansour, Haim Kaplan. 8210-8219 [doi]
- Predicting Choice with Set-Dependent AggregationNir Rosenfeld, Kojin Oshiba, Yaron Singer. 8220-8229 [doi]
- Certified Robustness to Label-Flipping Attacks via Randomized SmoothingElan Rosenfeld, Ezra Winston, Pradeep Ravikumar, Zico Kolter. 8230-8241 [doi]
- Revisiting Training Strategies and Generalization Performance in Deep Metric LearningKarsten Roth, Timo Milbich, Samarth Sinha, Prateek Gupta, Björn Ommer, Joseph Paul Cohen. 8242-8252 [doi]
- {FDaniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez 0001, Raman Arora. 8253-8265 [doi]
- Simple and sharp analysis of k-means||Václav Rozhon. 8266-8275 [doi]
- {BBin Xin Ru, Ahsan Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts. 8276-8285 [doi]
- Inter-domain Deep {GTim G. J. Rudner, Dino Sejdinovic, Yarin Gal. 8286-8294 [doi]
- Bio-Inspired Hashing for Unsupervised Similarity SearchChaitanya K. Ryali, John J. Hopfield, Leopold Grinberg, Dmitry Krotov. 8295-8306 [doi]
- Adversarial Attacks on Copyright Detection SystemsParsa Saadatpanah, Ali Shafahi, Tom Goldstein. 8307-8315 [doi]
- Bounding the fairness and accuracy of classifiers from population statisticsSivan Sabato, Elad Yom-Tov. 8316-8325 [doi]
- Radioactive data: tracing through trainingAlexandre Sablayrolles, Matthijs Douze, Cordelia Schmid, Hervé Jégou. 8326-8335 [doi]
- Causal Structure Discovery from Distributions Arising from Mixtures of {DAGBasil Saeed, Snigdha Panigrahi, Caroline Uhler. 8336-8345 [doi]
- An Investigation of Why Overparameterization Exacerbates Spurious CorrelationsShiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang. 8346-8356 [doi]
- Improved Sleeping Bandits with Stochastic Action Sets and Adversarial RewardsAadirupa Saha, Pierre Gaillard, Michal Valko. 8357-8366 [doi]
- From {PACAadirupa Saha, Aditya Gopalan. 8367-8376 [doi]
- Measuring Non-Expert Comprehension of Machine Learning Fairness MetricsDebjani Saha, Candice Schumann, Duncan C. McElfresh, John P. Dickerson, Michelle L. Mazurek, Michael Carl Tschantz. 8377-8387 [doi]
- From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular ModelsAytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause 0001. 8388-8397 [doi]
- Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference ModelsYuta Saito, Shota Yasui. 8398-8407 [doi]
- Inferring {DQNAndrey Sakryukin, Chedy Raissi, Mohan S. Kankanhalli. 8408-8416 [doi]
- The Performance Analysis of Generalized Margin Maximizers on Separable DataFariborz Salehi, Ehsan Abbasi, Babak Hassibi. 8417-8426 [doi]
- Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex OptimizationSudeep Salgia, Qing Zhao 0001, Sattar Vakili. 8427-8437 [doi]
- A Quantile-based Approach for Hyperparameter Transfer LearningDavid Salinas, Huibin Shen, Valerio Perrone. 8438-8448 [doi]
- Spectral Subsampling {MCMCRobert Salomone, Matias Quiroz, Robert Kohn, Mattias Villani, Minh-Ngoc Tran. 8449-8458 [doi]
- Learning to Simulate Complex Physics with Graph NetworksAlvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying, Jure Leskovec, Peter W. Battaglia. 8459-8468 [doi]
- The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient DescentKarthik Abinav Sankararaman, Soham De, Zheng Xu 0002, W. Ronny Huang, Tom Goldstein. 8469-8479 [doi]
- Explicit Gradient Learning for Black-Box OptimizationElad Sarafian, Mor Sinay, Yoram Louzoun, Noa Agmon, Sarit Kraus. 8480-8490 [doi]
- Detecting Out-of-Distribution Examples with {GChandramouli Shama Sastry, Sageev Oore. 8491-8501 [doi]
- Constrained {MHarsh Satija, Philip Amortila, Joelle Pineau. 8502-8511 [doi]
- A Sample Complexity Separation between Non-Convex and Convex Meta-LearningNikunj Saunshi, Yi Zhang, Mikhail Khodak, Sanjeev Arora. 8512-8521 [doi]
- Harmonic Decompositions of Convolutional NetworksMeyer Scetbon, Zaïd Harchaoui. 8522-8532 [doi]
- Implicit competitive regularization in {GANFlorian Schäfer, Hongkai Zheng, Animashree Anandkumar. 8533-8544 [doi]
- Off-Policy Actor-Critic with Shared Experience ReplaySimon Schmitt, Matteo Hessel, Karen Simonyan. 8545-8554 [doi]
- Discriminative Adversarial Search for Abstractive SummarizationThomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, Benjamin Piwowarski, Jacopo Staiano. 8555-8564 [doi]
- Universal Asymptotic Optimality of Polyak MomentumDamien Scieur, Fabian Pedregosa. 8565-8572 [doi]
- Random Matrix Theory Proves that Deep Learning Representations of {GANMohamed-El-Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain Couillet. 8573-8582 [doi]
- Planning to Explore via Self-Supervised World ModelsRamanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak. 8583-8592 [doi]
- An Explicitly Relational Neural Network ArchitectureMurray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David G. T. Barrett, Marta Garnelo. 8593-8603 [doi]
- Optimistic Policy Optimization with Bandit FeedbackLior Shani, Yonathan Efroni, Aviv Rosenberg 0002, Shie Mannor. 8604-8613 [doi]
- Neural Kernels Without TangentsVaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht. 8614-8623 [doi]
- Learning Robot Skills with Temporal Variational InferenceTanmay Shankar, Abhinav Gupta 0001. 8624-8633 [doi]
- Evaluating Machine Accuracy on {IVaishaal Shankar, Rebecca Roelofs, Horia Mania, Alex Fang, Benjamin Recht, Ludwig Schmidt. 8634-8644 [doi]
- Channel Equilibrium Networks for Learning Deep RepresentationWenqi Shao, Shitao Tang, Xingang Pan, Ping Tan, Xiaogang Wang 0001, Ping Luo 0002. 8645-8654 [doi]
- {CHuajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, Tarek F. Abdelzaher. 8655-8664 [doi]
- Lookahead-Bounded Q-learningIbrahim El Shar, Daniel R. Jiang. 8665-8675 [doi]
- Causal Strategic Linear RegressionYonadav Shavit, Benjamin L. Edelman, Brian Axelrod. 8676-8686 [doi]
- Adaptive Sampling for Estimating Probability DistributionsShubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh. 8687-8696 [doi]
- {PDOZhengyang Shen, Lingshen He, Zhouchen Lin, Jinwen Ma. 8697-8706 [doi]
- Deep Reinforcement Learning with Robust and Smooth PolicyQianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao. 8707-8718 [doi]
- Educating Text Autoencoders: Latent Representation Guidance via DenoisingTianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi Jaakkola. 8719-8729 [doi]
- Learning for Dose Allocation in Adaptive Clinical Trials with Safety ConstraintsCong Shen, Zhiyang Wang, Sofia S. Villar, Mihaela van der Schaar. 8730-8740 [doi]
- {PSheng Shen, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer. 8741-8751 [doi]
- Extreme Multi-label Classification from Aggregated LabelsYanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit S. Dhillon. 8752-8762 [doi]
- One-shot Distributed Ridge Regression in High DimensionsYue-sheng, Edgar Dobriban. 8763-8772 [doi]
- Landscape Connectivity and Dropout Stability of {SGDAlexander Shevchenko, Marco Mondelli. 8773-8784 [doi]
- Incremental Sampling Without Replacement for Sequence ModelsKensen Shi, David Bieber, Charles Sutton. 8785-8795 [doi]
- Message Passing Least Squares Framework and its Application to Rotation SynchronizationYunpeng Shi, Gilad Lerman. 8796-8806 [doi]
- Does the {MChengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng. 8807-8817 [doi]
- A Graph to Graphs Framework for Retrosynthesis PredictionChence Shi, Minkai Xu, Hongyu Guo, Ming Zhang 0004, Jian Tang. 8818-8827 [doi]
- Informative Dropout for Robust Representation Learning: A Shape-bias PerspectiveBaifeng Shi, Dinghuai Zhang, Qi Dai, Zhanxing Zhu, Yadong Mu, Jingdong Wang. 8828-8839 [doi]
- Dispersed Exponential Family Mixture {VAEWenxian Shi, Hao Zhou, Ning Miao, Lei Li 0005. 8840-8851 [doi]
- On Conditional Versus Marginal Bias in Multi-Armed BanditsJaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo. 8852-8861 [doi]
- Predictive Coding for Locally-Linear ControlRui Shu, Tung Nguyen, Yinlam Chow, Tuan Pham, Khoat Than, Mohammad Ghavamzadeh, Stefano Ermon, Hung Bui. 8862-8871 [doi]
- A {MSalman Sadiq Shuvo, Yasin Yilmaz, Alan Bush, Mark Hafen. 8872-8883 [doi]
- Distributionally Robust Policy Evaluation and Learning in Offline Contextual BanditsNian Si, Fan Zhang, Zhengyuan Zhou, Jose H. Blanchet. 8884-8894 [doi]
- Piecewise Linear Regression via a Difference of Convex FunctionsAli Siahkamari, Aditya Gangrade, Brian Kulis, Venkatesh Saligrama. 8895-8904 [doi]
- Learning Fair Policies in Multi-Objective ({DUmer Siddique, Paul Weng, Matthieu Zimmer. 8905-8915 [doi]
- Deep {GPer Sidén, Fredrik Lindsten. 8916-8926 [doi]
- Collaborative Machine Learning with Incentive-Aware Model RewardsRachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low. 8927-8936 [doi]
- Naive Exploration is Optimal for Online {LQRMax Simchowitz, Dylan J. Foster. 8937-8948 [doi]
- A Generative Model for Molecular Distance GeometryGregor N. C. Simm, José Miguel Hernández-Lobato. 8949-8958 [doi]
- Reinforcement Learning for Molecular Design Guided by Quantum MechanicsGregor N. C. Simm, Robert Pinsler, José Miguel Hernández-Lobato. 8959-8969 [doi]
- Fractional Underdamped {LUmut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gürbüzbalaban. 8970-8980 [doi]
- Second-Order Provable Defenses against Adversarial AttacksSahil Singla 0002, Soheil Feizi. 8981-8991 [doi]
- {FAman Sinha, Matthew O'Kelly, Hongrui Zheng, Rahul Mangharam, John C. Duchi, Russ Tedrake. 8992-9004 [doi]
- Small-{GANSamarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena. 9005-9015 [doi]
- Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device FailureJohn Sipple. 9016-9025 [doi]
- Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed AnalysisVidyashankar Sivakumar, Steven Wu, Arindam Banerjee. 9026-9035 [doi]
- Optimizer Benchmarking Needs to Account for Hyperparameter TuningPrabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret. 9036-9045 [doi]
- When Explanations Lie: Why Many Modified {BPLeon Sixt, Maximilian Granz, Tim Landgraf. 9046-9057 [doi]
- On the Generalization Benefit of Noise in Stochastic Gradient DescentSamuel L. Smith, Erich Elsen, Soham De. 9058-9067 [doi]
- Multiclass Neural Network Minimization via Tropical {NGeorgios Smyrnis, Petros Maragos. 9068-9077 [doi]
- Bridging the Gap Between f-{GANJiaming Song, Stefano Ermon. 9078-9087 [doi]
- Provably Efficient Model-based Policy AdaptationYuda Song, Aditi Mavalankar, Wen Sun, Sicun Gao. 9088-9098 [doi]
- Hypernetwork approach to generating point cloudsPrzemyslaw Spurek, Sebastian Winczowski, Jacek Tabor, Maciej Zamorski, Maciej Zieba, Tomasz Trzcinski. 9099-9108 [doi]
- Robustness to Spurious Correlations via Human AnnotationsMegha Srivastava, Tatsunori B. Hashimoto, Percy Liang. 9109-9119 [doi]
- Which Tasks Should Be Learned Together in Multi-task Learning?Trevor Standley, Amir Roshan Zamir, Dawn Chen, Leonidas J. Guibas, Jitendra Malik, Silvio Savarese. 9120-9132 [doi]
- Responsive Safety in Reinforcement Learning by {PIDAdam Stooke, Joshua Achiam, Pieter Abbeel. 9133-9143 [doi]
- Learning Discrete Structured Representations by Adversarially Maximizing Mutual InformationKarl Stratos, Sam Wiseman. 9144-9154 [doi]
- Confidence-Calibrated Adversarial Training: Generalizing to Unseen AttacksDavid Stutz, Matthias Hein 0001, Bernt Schiele. 9155-9166 [doi]
- Doubly robust off-policy evaluation with shrinkageYi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miroslav Dudík. 9167-9176 [doi]
- Task Understanding from Confusing Multi-task DataXin Su, Yizhou Jiang, Shangqi Guo, Feng Chen. 9177-9186 [doi]
- {CDijia Su, Jayden Ooi, Tyler Lu, Dale Schuurmans, Craig Boutilier. 9187-9195 [doi]
- Adaptive Estimator Selection for Off-Policy EvaluationYi Su, Pavithra Srinath, Akshay Krishnamurthy. 9196-9205 [doi]
- Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training DataFelipe Petroski Such, Aditya Rawal, Joel Lehman, Kenneth O. Stanley, Jeffrey Clune. 9206-9216 [doi]
- Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and TrackingHaoran Sun, Songtao Lu, Mingyi Hong. 9217-9228 [doi]
- Test-Time Training with Self-Supervision for Generalization under Distribution ShiftsYu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt. 9229-9248 [doi]
- An {EMZhiqing Sun, Yiming Yang. 9249-9258 [doi]
- The Shapley Taylor Interaction IndexMukund Sundararajan, Kedar Dhamdhere, Ashish Agarwal. 9259-9268 [doi]
- The Many Shapley Values for Model ExplanationMukund Sundararajan, Amir Najmi. 9269-9278 [doi]
- Multi-objective {BShinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama. 9279-9288 [doi]
- The k-tied Normal Distribution: A Compact Parameterization of {GJakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin. 9289-9299 [doi]
- Multi-Agent Routing Value Iteration NetworkQuinlan Sykora, Mengye Ren, Raquel Urtasun. 9300-9310 [doi]
- Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal DiscoveryNatasa Tagasovska, Valérie Chavez-Demoulin, Thibault Vatter. 9311-9323 [doi]
- Quantized Decentralized Stochastic Learning over Directed GraphsHossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani. 9324-9333 [doi]
- Multi-fidelity {BShion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama. 9334-9345 [doi]
- Fiedler Regularization: Learning Neural Networks with Graph SparsityEdric Tam, David Dunson. 9346-9355 [doi]
- {DChong Min John Tan, Mehul Motani. 9356-9366 [doi]
- Reinforcement Learning for Integer Programming: Learning to CutYunhao Tang, Shipra Agrawal 0001, Yuri Faenza. 9367-9376 [doi]
- The Buckley-Osthus model and the block preferential attachment model: statistical analysis and applicationWenpin Tang, Xin Guo, Fengmin Tang. 9377-9386 [doi]
- Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued PoliciesShengpu Tang, Aditya Modi 0002, Michael W. Sjoding, Jenna Wiens. 9387-9396 [doi]
- Taylor Expansion Policy OptimizationYunhao Tang, Michal Valko, Rémi Munos. 9397-9406 [doi]
- Variational Imitation Learning with Diverse-quality DemonstrationsVoot Tangkaratt, Bo Han 0003, Mohammad Emtiyaz Khan, Masashi Sugiyama. 9407-9417 [doi]
- Learning disconnected manifolds: a no {GANUgo Tanielian, Thibaut Issenhuth, Elvis Dohmatob, Jérémie Mary. 9418-9427 [doi]
- No-Regret Exploration in Goal-Oriented Reinforcement LearningJean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric. 9428-9437 [doi]
- Sparse {SYi Tay, Dara Bahri, Liu Yang, Donald Metzler, Da-Cheng Juan. 9438-9447 [doi]
- Inductive Relation Prediction by Subgraph ReasoningKomal Teru, Etienne Denis, Will Hamilton. 9448-9457 [doi]
- Few-shot Domain Adaptation by Causal Mechanism TransferTakeshi Teshima, Issei Sato, Masashi Sugiyama. 9458-9469 [doi]
- Student Specialization in Deep Rectified Networks With Finite Width and Input DimensionYuandong Tian. 9470-9480 [doi]
- Sequential Transfer in Reinforcement Learning with a Generative ModelAndrea Tirinzoni, Riccardo Poiani, Marcello Restelli. 9481-9492 [doi]
- Convolutional dictionary learning based auto-encoders for natural exponential-family distributionsBahareh Tolooshams, Andrew H. Song, Simona Temereanca, Demba E. Ba. 9493-9503 [doi]
- Multi-step Greedy Reinforcement Learning AlgorithmsManan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh. 9504-9513 [doi]
- Choice Set Optimization Under Discrete Choice Models of Group DecisionsKiran Tomlinson, Austin R. Benson. 9514-9525 [doi]
- {TAlexander Tong 0001, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy. 9526-9536 [doi]
- Alleviating Privacy Attacks via Causal LearningShruti Tople, Amit Sharma, Aditya Nori. 9537-9547 [doi]
- {BCsaba Tóth, Harald Oberhauser. 9548-9560 [doi]
- Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial PerturbationsFlorian Tramèr, Jens Behrmann, Nicholas Carlini, Nicolas Papernot, Jörn-Henrik Jacobsen. 9561-9571 [doi]
- Stochastic {GQuoc Tran-Dinh, Nhan H. Pham, Lam M. Nguyen. 9572-9582 [doi]
- {BAleksei Triastcyn, Boi Faltings. 9583-9592 [doi]
- Single Point Transductive PredictionNilesh Tripuraneni, Lester Mackey. 9593-9602 [doi]
- {GRakshit Trivedi, Jiachen Yang, Hongyuan Zha. 9603-9613 [doi]
- Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited ResourcesYun-Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho. 9614-9624 [doi]
- From {IDimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry. 9625-9635 [doi]
- Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using {PACYusuke Tsuzuku, Issei Sato, Masashi Sugiyama. 9636-9647 [doi]
- Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural NetworkJavier Turek, Shailee Jain, Vy A. Vo, Mihai Capota, Alexander Huth, Theodore L. Willke. 9648-9658 [doi]
- Minimax Weight and Q-Function Learning for Off-Policy EvaluationMasatoshi Uehara, Jiawei Huang, Nan Jiang. 9659-9668 [doi]
- {SAleksei Ustimenko, Liudmila Prokhorenkova. 9669-9679 [doi]
- Undirected Graphical Models as Approximate PosteriorsArash Vahdat, Evgeny Andriyash, William G. Macready. 9680-9689 [doi]
- Uncertainty Estimation Using a Single Deep Deterministic Neural NetworkJoost van Amersfoort, Lewis Smith, Yee Whye Teh, Yarin Gal. 9690-9700 [doi]
- Deep Molecular Programming: A Natural Implementation of Binary-Weight {RMarko Vasic, Cameron T. Chalk, Sarfraz Khurshid, David Soloveichik. 9701-9711 [doi]
- Linear bandits with Stochastic Delayed FeedbackClaire Vernade, Alexandra Carpentier, Tor Lattimore, Giovanni Zappella, Beyza Ermis, Michael Brückner. 9712-9721 [doi]
- Non-Stationary Delayed Bandits with Intermediate ObservationsClaire Vernade, András György 0001, Timothy A. Mann. 9722-9732 [doi]
- {OPAlexander Vezhnevets, Yuhuai Wu, Maria Eckstein, Rémi Leblond, Joel Z. Leibo. 9733-9742 [doi]
- Born-Again Tree EnsemblesThibaut Vidal, Maximilian Schiffer. 9743-9753 [doi]
- Private Reinforcement Learning with {PACGiuseppe Vietri, Borja Balle, Akshay Krishnamurthy, Zhiwei Steven Wu. 9754-9764 [doi]
- New Oracle-Efficient Algorithms for Private Synthetic Data ReleaseGiuseppe Vietri, Grace Tian, Mark Bun, Thomas Steinke, Zhiwei Steven Wu. 9765-9774 [doi]
- Conditional gradient methods for stochastically constrained convex minimizationMaria-Luiza Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher. 9775-9785 [doi]
- Unsupervised Discovery of Interpretable Directions in the {GANAndrey Voynov, Artem Babenko. 9786-9796 [doi]
- Safe Reinforcement Learning in Constrained {MAkifumi Wachi, Yanan Sui. 9797-9806 [doi]
- Orthogonalized {SGDChengcheng Wan, Henry Hoffmann, Shan Lu 0001, Michael Maire. 9807-9817 [doi]
- Projection-free Distributed Online Convex Optimization with $O(\sqrt{TYuanyu Wan, Wei-Wei Tu, Lijun Zhang 0005. 9818-9828 [doi]
- Logistic Regression for Massive Data with Rare EventsHaiying Wang. 9829-9836 [doi]
- On the Global Optimality of Model-Agnostic Meta-LearningLingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang. 9837-9846 [doi]
- Towards Accurate Post-training Network Quantization via Bit-Split and StitchingPeisong Wang, Qiang Chen, Xiangyu He, Jian Cheng. 9847-9856 [doi]
- Self-Modulating Nonparametric Event-Tensor FactorizationZheng Wang, Xinqi Chu, Shandian Zhe. 9857-9867 [doi]
- Upper bounds for Model-Free Row-Sparse Principal Component AnalysisGuanyi Wang, Santanu S. Dey. 9868-9875 [doi]
- {ROMATonghan Wang 0001, Heng Dong, Victor R. Lesser, Chongjie Zhang. 9876-9886 [doi]
- Non-separable Non-stationary random fieldsKangrui Wang, Oliver Hamelijnck, Theodoros Damoulas, Mark F. J. Steel. 9887-9897 [doi]
- Continuously Indexed Domain AdaptationHao Wang, Hao He, Dina Katabi. 9898-9907 [doi]
- Learning Efficient Multi-agent Communication: An Information Bottleneck ApproachRundong Wang, Xu He, Runsheng Yu, Wei Qiu, Bo An 0001, Zinovi Rabinovich. 9908-9918 [doi]
- Frustratingly Simple Few-Shot Object DetectionXin Wang, Thomas E. Huang, Joseph Gonzalez 0001, Trevor Darrell, Fisher Yu. 9919-9928 [doi]
- Understanding Contrastive Representation Learning through Alignment and Uniformity on the HypersphereTongzhou Wang 0001, Phillip Isola. 9929-9939 [doi]
- Enhanced {POETRui Wang 0052, Joel Lehman, Aditya Rawal, Jiale Zhi, Yulun Li, Jeffrey Clune, Kenneth O. Stanley. 9940-9951 [doi]
- Haar Graph PoolingYu Guang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan. 9952-9962 [doi]
- Deep Streaming Label LearningZhen Wang, Liu Liu, Dacheng Tao. 9963-9972 [doi]
- {BXiaochen Wang, Arash Pakbin, Bobak Mortazavi, Hongyu Zhao, Donald K. K. Lee. 9973-9982 [doi]
- Optimizing Data Usage via Differentiable RewardsXinyi Wang, Hieu Pham, Paul Michel, Antonios Anastasopoulos, Jaime G. Carbonell, Graham Neubig. 9983-9995 [doi]
- Bandits for {BMOTianyu Wang, Cynthia Rudin. 9996-10006 [doi]
- When deep denoising meets iterative phase retrievalYaotian Wang, Xiaohang Sun, Jason W. Fleischer. 10007-10017 [doi]
- Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent VariablesQi Wang, Herke van Hoof. 10018-10028 [doi]
- Loss Function Search for Face RecognitionXiaobo Wang, Shuo Wang, Cheng Chi, Shifeng Zhang, Tao Mei 0001. 10029-10038 [doi]
- Sequential Cooperative {BJunqi Wang, Pei Wang, Patrick Shafto. 10039-10049 [doi]
- Neural Network Control Policy Verification With Persistent Adversarial PerturbationYuh-Shyang Wang, Lily Weng, Luca Daniel. 10050-10059 [doi]
- Cost-effectively Identifying Causal Effects When Only Response Variable is ObservableTian-Zuo Wang, Xi-Zhu Wu, Sheng-Jun Huang, Zhi-Hua Zhou. 10060-10069 [doi]
- Striving for Simplicity and Performance in Off-Policy {DRLChe Wang, Yanqiu Wu, Quan Vuong, Keith Ross. 10070-10080 [doi]
- On Differentially Private Stochastic Convex Optimization with Heavy-tailed DataDi Wang 0015, Hanshen Xiao, Srinivas Devadas, Jinhui Xu 0001. 10081-10091 [doi]
- Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement LearningLingxiao Wang, Zhuoran Yang, Zhaoran Wang. 10092-10103 [doi]
- On Lp-norm Robustness of Ensemble Decision Stumps and TreesYihan Wang, Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh. 10104-10114 [doi]
- Thompson Sampling via Local UncertaintyZhendong Wang, Mingyuan Zhou. 10115-10125 [doi]
- A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block ModelPeng Wang, Zirui Zhou, Anthony Man-Cho So. 10126-10135 [doi]
- Learning Representations that Support ExtrapolationTaylor W. Webb, Zachary Dulberg, Steven Frankland, Alexander A. Petrov, Randall C. O'Reilly, Jonathan Cohen. 10136-10146 [doi]
- {PFeng Wei. 10147-10157 [doi]
- Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging ProblemsKaixuan Wei, Angelica I. Avilés-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, Hua Huang 0001. 10158-10169 [doi]
- Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision ProcessesChen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo, Hiteshi Sharma, Rahul Jain 0002. 10170-10180 [doi]
- The Implicit and Explicit Regularization Effects of DropoutColin Wei, Sham M. Kakade, Tengyu Ma. 10181-10192 [doi]
- Online Control of the False Coverage Rate and False Sign RateAsaf Weinstein, Aaditya Ramdas. 10193-10202 [doi]
- Batch Stationary Distribution EstimationJunfeng Wen, Bo Dai, Lihong Li 0001, Dale Schuurmans. 10203-10213 [doi]
- Domain Aggregation Networks for Multi-Source Domain AdaptationJunfeng Wen, Russell Greiner, Dale Schuurmans. 10214-10224 [doi]
- Towards Understanding the Regularization of Adversarial Robustness on Neural NetworksYuxin Wen, Shuai Li, Kui Jia. 10225-10235 [doi]
- Amortised Learning by Wake-SleepLi K. Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani. 10236-10247 [doi]
- How Good is the Bayes Posterior in Deep Neural Networks Really?Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin. 10248-10259 [doi]
- Predictive Sampling with Forecasting Autoregressive ModelsAuke J. Wiggers, Emiel Hoogeboom. 10260-10269 [doi]
- State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian ProcessesWilliam J. Wilkinson, Paul E. Chang, Michael Riis Andersen, Arno Solin. 10270-10281 [doi]
- Efficient nonparametric statistical inference on population feature importance using Shapley valuesBrian D. Williamson, Jean Feng. 10282-10291 [doi]
- Efficiently sampling functions from Gaussian process posteriorsJames T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth. 10292-10302 [doi]
- Learning to Rank Learning CurvesMartin Wistuba, Tejaswini Pedapati. 10303-10312 [doi]
- Causal Inference using Gaussian Processes with Structured Latent ConfoundersSam Witty, Kenta Takatsu, David D. Jensen, Vikash Mansinghka. 10313-10323 [doi]
- Near Input Sparsity Time Kernel Embeddings via Adaptive SamplingDavid P. Woodruff, Amir Zandieh. 10324-10333 [doi]
- Is Local SGD Better than Minibatch SGD?Blake E. Woodworth, Kumar Kshitij Patel, Sebastian U. Stich, Zhen Dai, Brian Bullins, H. Brendan McMahan, Ohad Shamir, Nathan Srebro. 10334-10343 [doi]
- Obtaining Adjustable Regularization for Free via Iterate AveragingJingfeng Wu, Vladimir Braverman, Lin Yang. 10344-10354 [doi]
- DeltaGrad: Rapid retraining of machine learning modelsYinjun Wu, Edgar Dobriban, Susan B. Davidson. 10355-10366 [doi]
- On the Noisy Gradient Descent that Generalizes as SGDJingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Vladimir Braverman, Zhanxing Zhu. 10367-10376 [doi]
- Stronger and Faster Wasserstein Adversarial AttacksKaiwen Wu, Allen Houze Wang, Yaoliang Yu. 10377-10387 [doi]
- Sequence Generation with Mixed RepresentationsLijun Wu, Shufang Xie 0003, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tie-Yan Liu. 10388-10398 [doi]
- Adversarial Robustness via Runtime Masking and CleansingYi Hsuan Wu, Chia-Hung Yuan, Shan-Hung Wu. 10399-10409 [doi]
- On the Generalization Effects of Linear Transformations in Data AugmentationSen Wu, Hongyang Zhang, Gregory Valiant, Christopher Ré. 10410-10420 [doi]
- Amortized Population Gibbs Samplers with Neural Sufficient StatisticsHao Wu 0020, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem van de Meent. 10421-10431 [doi]
- Continuous Graph Neural NetworksLouis-Pascal A. C. Xhonneux, Meng Qu, Jian Tang. 10432-10441 [doi]
- A Flexible Framework for Nonparametric Graphical Modeling that Accommodates Machine LearningYunhua Xiang, Noah Simon. 10442-10451 [doi]
- Generative Flows with Matrix ExponentialChangyi Xiao, Ligang Liu. 10452-10461 [doi]
- Disentangling Trainability and Generalization in Deep Neural NetworksLechao Xiao, Jeffrey Pennington, Samuel Schoenholz. 10462-10472 [doi]
- Optimally Solving Two-Agent Decentralized POMDPs Under One-Sided Information SharingYuxuan Xie, Jilles Dibangoye, Olivier Buffet. 10473-10482 [doi]
- Maximum-and-Concatenation NetworksXingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin. 10483-10494 [doi]
- Zeno++: Robust Fully Asynchronous SGDCong Xie, Sanmi Koyejo, Indranil Gupta. 10495-10503 [doi]
- Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization ProblemsGuangzeng Xie, Luo Luo, Yijiang Lian, Zhihua Zhang. 10504-10513 [doi]
- On the Number of Linear Regions of Convolutional Neural NetworksHuan Xiong, Lei Huang, Mengyang Yu, Li Liu 0004, Fan Zhu 0001, Ling Shao 0001. 10514-10523 [doi]
- On Layer Normalization in the Transformer ArchitectureRuibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu. 10524-10533 [doi]
- On Variational Learning of Controllable Representations for Text without SupervisionPeng Xu, Jackie Chi Kit Cheung, Yanshuai Cao. 10534-10543 [doi]
- Class-Weighted Classification: Trade-offs and Robust ApproachesZiyu Xu, Chen Dan 0001, Justin Khim, Pradeep Ravikumar. 10544-10554 [doi]
- A Finite-Time Analysis of Q-Learning with Neural Network Function ApproximationPan Xu 0002, Quanquan Gu. 10555-10565 [doi]
- Understanding and Stabilizing GANs' Training Dynamics Using Control TheoryKun Xu 0004, Chongxuan Li, Jun Zhu, Bo Zhang 0010. 10566-10575 [doi]
- Learning Autoencoders with Relational RegularizationHongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin. 10576-10586 [doi]
- Learning Factorized Weight Matrix for Joint FilteringXiangyu Xu, Yongrui Ma, Wenxiu Sun. 10587-10596 [doi]
- Variational Label EnhancementNing Xu 0009, Jun Shu, Yun-peng Liu, Xin Geng. 10597-10606 [doi]
- Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot ControlJie Xu, Yunsheng Tian, Pingchuan Ma0002, Daniela Rus, Shinjiro Sueda, Wojciech Matusik. 10607-10616 [doi]
- MetaFun: Meta-Learning with Iterative Functional UpdatesJin Xu, Jean-Francois Ton, Hyunjik Kim, Adam R. Kosiorek, Yee Whye Teh. 10617-10627 [doi]
- Video Prediction via Example GuidanceJingwei Xu, Huazhe Xu, Bingbing Ni, Xiaokang Yang, Trevor Darrell. 10628-10637 [doi]
- Amortized Finite Element Analysis for Fast PDE-Constrained OptimizationTianju Xue, Alex Beatson, Sigrid Adriaenssens, Ryan P. Adams. 10638-10647 [doi]
- Feature Selection using Stochastic GatesYutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger. 10648-10659 [doi]
- Stochastic Optimization for Non-convex Inf-Projection ProblemsYan Yan 0006, Yi Xu, Lijun Zhang, Xiaoyu Wang, Tianbao Yang. 10660-10669 [doi]
- Variational Bayesian QuantizationYibo Yang, Robert Bamler, Stephan Mandt. 10670-10680 [doi]
- Energy-Based Processes for Exchangeable DataMengjiao Yang, Bo Dai, Hanjun Dai, Dale Schuurmans. 10681-10692 [doi]
- Randomized Smoothing of All Shapes and SizesGreg Yang, Tony Duan, J. Edward Hu, Hadi Salman, Ilya P. Razenshteyn, Jerry Li 0001. 10693-10705 [doi]
- Q-value Path Decomposition for Deep Multiagent Reinforcement LearningYaodong Yang, Jianye Hao, Guangyong Chen, Hongyao Tang, Yingfeng Chen, Yujing Hu, Changjie Fan, Zhongyu Wei. 10706-10715 [doi]
- Improving Molecular Design by Stochastic Iterative Target AugmentationKevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi S. Jaakkola. 10716-10726 [doi]
- On the consistency of top-k surrogate lossesForest Yang, Sanmi Koyejo. 10727-10735 [doi]
- Interpolation between Residual and Non-Residual NetworksZonghan Yang, Yang Liu, Chenglong Bao, Zuoqiang Shi. 10736-10745 [doi]
- Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret BoundLin Yang, Mengdi Wang. 10746-10756 [doi]
- Multi-Agent Determinantal Q-LearningYaodong Yang, Ying Wen, Jun Wang 0012, Liheng Chen, Kun Shao, David Mguni, Weinan Zhang 0001. 10757-10766 [doi]
- Rethinking Bias-Variance Trade-off for Generalization of Neural NetworksZitong Yang, Yaodong Yu, Chong You, Jacob Steinhardt, Yi Ma. 10767-10777 [doi]
- Unsupervised Transfer Learning for Spatiotemporal Predictive NetworksZhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang. 10778-10788 [doi]
- Searching to Exploit Memorization Effect in Learning with Noisy LabelsQuanming Yao, Hansi Yang, Bo Han 0003, Gang Niu 0001, James Tin-Yau Kwok. 10789-10798 [doi]
- Graph-based, Self-Supervised Program Repair from Diagnostic FeedbackMichihiro Yasunaga, Percy Liang. 10799-10808 [doi]
- Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text ClassificationHui Ye, ZhiYu Chen, Da-Han Wang, Brian D. Davison. 10809-10819 [doi]
- Good Subnetworks Provably Exist: Pruning via Greedy Forward SelectionMao Ye, ChengYue Gong, Lizhen Nie, Denny Zhou, Adam Klivans, Qiang Liu. 10820-10830 [doi]
- It's Not What Machines Can Learn, It's What We Cannot TeachGal Yehuda, Moshe Gabel, Assaf Schuster. 10831-10841 [doi]
- Data Valuation using Reinforcement LearningJinsung Yoon, Sercan Ömer Arik, Tomas Pfister. 10842-10851 [doi]
- XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot LearningSung Whan Yoon, Do Yeon Kim, Jun Seo, Jaekyun Moon. 10852-10860 [doi]
- Robustifying Sequential Neural ProcessesJaesik Yoon, Gautam Singh, Sungjin Ahn. 10861-10870 [doi]
- When Does Self-Supervision Help Graph Convolutional Networks?Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen. 10871-10880 [doi]
- Graph Structure of Neural NetworksJiaxuan You, Jure Leskovec, Kaiming He, Saining Xie. 10881-10891 [doi]
- Simultaneous Inference for Massive Data: Distributed BootstrapYang Yu, Shih-Kang Chao, Guang Cheng. 10892-10901 [doi]
- Graphical Models Meet Bandits: A Variational Thompson Sampling ApproachTong Yu 0001, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel. 10902-10912 [doi]
- Label-Noise Robust Domain AdaptationXiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang 0001, Kayhan Batmanghelich, Dacheng Tao. 10913-10924 [doi]
- Intrinsic Reward Driven Imitation Learning via Generative ModelXingrui Yu, Yueming Lyu, Ivor W. Tsang. 10925-10935 [doi]
- Graph Convolutional Network for Recommendation with Low-pass Collaborative FiltersWenhui Yu, Zheng Qin. 10936-10945 [doi]
- Federated Learning with Only Positive LabelsFelix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar. 10946-10956 [doi]
- Training Deep Energy-Based Models with f-Divergence MinimizationLantao Yu, Yang Song 0011, Jiaming Song, Stefano Ermon. 10957-10967 [doi]
- Graph Random Neural Features for Distance-Preserving Graph RepresentationsDaniele Zambon, Cesare Alippi, Lorenzo Livi. 10968-10977 [doi]
- Learning Near Optimal Policies with Low Inherent Bellman ErrorAndrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill. 10978-10989 [doi]
- Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message PassingZhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck. 10990-11000 [doi]
- Learning Calibratable Policies using Programmatic Style-ConsistencyEric Zhan, Albert Tseng, Yisong Yue, Adith Swaminathan, Matthew J. Hausknecht. 11001-11011 [doi]
- Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning ApproachJunzhe Zhang. 11012-11022 [doi]
- Robustness to Programmable String Transformations via Augmented Abstract TrainingYuhao Zhang, Aws Albarghouthi, Loris D'Antoni. 11023-11032 [doi]
- Converging to Team-Maxmin Equilibria in Zero-Sum Multiplayer GamesYouzhi Zhang 0004, Bo An 0001. 11033-11043 [doi]
- Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence RateYufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang. 11044-11054 [doi]
- Cautious Adaptation For Reinforcement Learning in Safety-Critical SettingsJesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman. 11055-11065 [doi]
- Learning the Valuations of a k-demand AgentHanrui Zhang, Vincent Conitzer. 11066-11075 [doi]
- A Tree-Structured Decoder for Image-to-Markup GenerationJianshu Zhang, Jun Du, Yongxin Yang, Yi-Zhe Song, Si Wei, Lirong Dai 0001. 11076-11085 [doi]
- Approximation Capabilities of Neural ODEs and Invertible Residual NetworksHan Zhang, Xi Gao, Jacob Unterman, Tom Arodz. 11086-11095 [doi]
- Random Hypervolume Scalarizations for Provable Multi-Objective Black Box OptimizationRichard Zhang, Daniel Golovin. 11096-11105 [doi]
- Spread DivergenceMingtian Zhang, Peter Hayes, Thomas Bird, Raza Habib, David Barber. 11106-11116 [doi]
- Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep LearningJize Zhang, Bhavya Kailkhura, T. Yong-Jin Han. 11117-11128 [doi]
- Privately Learning Markov Random FieldsHuanyu Zhang, Gautam Kamath 0001, Janardhan Kulkarni, Zhiwei Steven Wu. 11129-11140 [doi]
- Learning Structured Latent Factors from Dependent Data: A Generative Model Framework from Information-Theoretic PerspectiveRuixiang Zhang, Masanori Koyama, Katsuhiko Ishiguro. 11141-11152 [doi]
- Optimal Estimator for Unlabeled Linear RegressionHang Zhang, Ping Li. 11153-11162 [doi]
- Dual-Path Distillation: A Unified Framework to Improve Black-Box AttacksYonggang Zhang, Ya Li, Tongliang Liu, Xinmei Tian. 11163-11172 [doi]
- Complexity of Finding Stationary Points of Nonconvex Nonsmooth FunctionsJingzhao Zhang, Hongzhou Lin, Stefanie Jegelka, Suvrit Sra, Ali Jadbabaie. 11173-11182 [doi]
- Self-Attentive Hawkes ProcessQiang Zhang, Aldo Lipani, Ömer Kirnap, Emine Yilmaz. 11183-11193 [doi]
- GradientDICE: Rethinking Generalized Offline Estimation of Stationary ValuesShangtong Zhang, Bo Liu, Shimon Whiteson. 11194-11203 [doi]
- Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function ApproximationShangtong Zhang, Bo Liu, Hengshuai Yao, Shimon Whiteson. 11204-11213 [doi]
- Invariant Causal Prediction for Block MDPsAmy Zhang 0001, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup. 11214-11224 [doi]
- Adaptive Reward-Poisoning Attacks against Reinforcement LearningXuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu 0001. 11225-11234 [doi]
- CAUSE: Learning Granger Causality from Event Sequences using Attribution MethodsWei Zhang 0058, Thomas Kobber Panum, Somesh Jha, Prasad Chalasani, David Page. 11235-11245 [doi]
- Convex Calibrated Surrogates for the Multi-Label F-MeasureMingyuan Zhang, Harish Guruprasad Ramaswamy, Shivani Agarwal 0001. 11246-11255 [doi]
- Sparsified Linear Programming for Zero-Sum Equilibrium FindingBrian Hu Zhang, Tuomas Sandholm. 11256-11267 [doi]
- Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer CaseShuai Zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong. 11268-11277 [doi]
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- A Flexible Latent Space Model for Multilayer NetworksXuefei Zhang, Songkai Xue, Ji Zhu. 11288-11297 [doi]
- Perceptual Generative AutoencodersZijun Zhang, Ruixiang Zhang, Zongpeng Li, Yoshua Bengio, Liam Paull. 11298-11306 [doi]
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- Learning with Feature and Distribution Evolvable StreamsZhenyu Zhang, Peng Zhao 0006, Yuan Jiang, Zhi-Hua Zhou. 11317-11327 [doi]
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- On Learning Language-Invariant Representations for Universal Machine TranslationHan Zhao 0002, Junjie Hu, Andrej Risteski. 11352-11364 [doi]
- Do RNN and LSTM have Long Memory?Jingyu Zhao 0001, Feiqing Huang, Jia Lv, Yanjie Duan, Zhen Qin, Guodong Li, Guangjian Tian. 11365-11375 [doi]
- Feature Quantization Improves GAN TrainingYang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen. 11376-11386 [doi]
- Individual Calibration with Randomized ForecastingShengjia Zhao, Tengyu Ma, Stefano Ermon. 11387-11397 [doi]
- Smaller, more accurate regression forests using tree alternating optimizationArman Zharmagambetov, Miguel Á. Carreira-Perpinan. 11398-11408 [doi]
- Learning to Learn Kernels with Variational Random FeaturesXiantong Zhen, Haoliang Sun, Ying-jun Du, Jun Xu, Yilong Yin, Ling Shao 0001, Cees Snoek. 11409-11419 [doi]
- Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth ExpansionQinqing Zheng, Jinshuo Dong, Qi Long, Weijie Su. 11420-11435 [doi]
- What Can Learned Intrinsic Rewards Capture?Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh. 11436-11446 [doi]
- Error-Bounded Correction of Noisy LabelsSongzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami 0001, Dimitris N. Metaxas, Chao Chen. 11447-11457 [doi]
- Robust Graph Representation Learning via Neural SparsificationCheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang 0010. 11458-11468 [doi]
- Bisection-Based Pricing for Repeated Contextual Auctions against Strategic BuyerAnton Zhiyanov, Alexey Drutsa. 11469-11480 [doi]
- Best Arm Identification for Cascading Bandits in the Fixed Confidence SettingZixin Zhong, Wang Chi Cheung, Vincent Y. F. Tan. 11481-11491 [doi]
- Neural Contextual Bandits with UCB-based ExplorationDongruo Zhou, Lihong Li 0001, Quanquan Gu. 11492-11502 [doi]
- MoNet3D: Towards Accurate Monocular 3D Object Localization in Real TimeXichuan Zhou, Yicong Peng, Chunqiao Long, Fengbo Ren, Cong Shi. 11503-11512 [doi]
- Nonparametric Score EstimatorsYuhao Zhou, Jiaxin Shi, Jun Zhu. 11513-11522 [doi]
- Time-Consistent Self-Supervision for Semi-Supervised LearningTianyi Zhou, Shengjie Wang, Jeff A. Bilmes. 11523-11533 [doi]
- Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic SupportYuan Zhou, Hongseok Yang, Yee Whye Teh, Tom Rainforth. 11534-11545 [doi]
- Go Wide, Then Narrow: Efficient Training of Deep Thin NetworksDenny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans. 11546-11555 [doi]
- Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal GeneralizationPan Zhou, Xiao-Tong Yuan. 11556-11565 [doi]
- Robust Outlier Arm IdentificationYinglun Zhu, Sumeet Katariya, Robert D. Nowak. 11566-11575 [doi]
- Variance Reduction and Quasi-Newton for Particle-Based Variational InferenceMichael Zhu, Chang Liu, Jun Zhu. 11576-11587 [doi]
- Causal Effect Estimation and Optimal Dose Suggestions in Mobile HealthLiangyu Zhu, Wenbin Lu, Rui Song. 11588-11598 [doi]
- Thompson Sampling Algorithms for Mean-Variance BanditsQiuyu Zhu, Vincent Y. F. Tan. 11599-11608 [doi]
- Learning Adversarially Robust Representations via Worst-Case Mutual Information MaximizationSicheng Zhu, Xiao Zhang, David Evans 0001. 11609-11618 [doi]
- Linear Convergence of Randomized Primal-Dual Coordinate Method for Large-scale Linear Constrained Convex ProgrammingDaoli Zhu, Lei Zhao. 11619-11628 [doi]
- When Demands Evolve Larger and Noisier: Learning and Earning in a Growing EnvironmentFeng Zhu, Zeyu Zheng. 11629-11638 [doi]
- Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODEJuntang Zhuang, Nicha C. Dvornek, Xiaoxiao Li, Sekhar Tatikonda, Xenophon Papademetris, James S. Duncan. 11639-11649 [doi]
- Learning Optimal Tree Models under Beam SearchJingwei Zhuo, Ziru Xu, Wei Dai, Han Zhu, Han Li, Jian Xu, Kun Gai. 11650-11659 [doi]
- Laplacian Regularized Few-Shot LearningImtiaz Masud Ziko, Jose Dolz, Eric Granger, Ismail Ben Ayed. 11660-11670 [doi]
- Influenza Forecasting Framework based on Gaussian ProcessesChristoph Zimmer, Reza Yaesoubi. 11671-11679 [doi]
- A general recurrent state space framework for modeling neural dynamics during decision-makingDavid M. Zoltowski, Jonathan W. Pillow, Scott W. Linderman. 11680-11691 [doi]
- Transformer Hawkes ProcessSimiao Zuo, Haoming Jiang, Zichong Li, Tuo Zhao, Hongyuan Zha. 11692-11702 [doi]