Abstract is missing.
- On the Effect of Auxiliary Tasks on Representation DynamicsClare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney. 1-9 [doi]
- LassoNet: Neural Networks with Feature SparsityIsmael Lemhadri, Feng Ruan, Robert Tibshirani. 10-18 [doi]
- Projection-Free Optimization on Uniformly Convex SetsThomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta. 19-27 [doi]
- Differentiable Greedy Algorithm for Monotone Submodular Maximization: Guarantees, Gradient Estimators, and ApplicationsShinsaku Sakaue. 28-36 [doi]
- Graphical Normalizing FlowsAntoine Wehenkel, Gilles Louppe. 37-45 [doi]
- One-Round Communication Efficient Distributed M-EstimationYajie Bao, Weijia Xiong. 46-54 [doi]
- CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel MatricesValerii Likhosherstov, Jared Davis, Krzysztof Choromanski, Adrian Weller. 55-63 [doi]
- Regularized Policies are Reward RobustHisham Husain, Kamil Ciosek, Ryota Tomioka. 64-72 [doi]
- Semi-Supervised Learning with Meta-GradientTaihong Xiao, Xin-yu Zhang, Hao-Lin Jia, Ming-Ming Cheng, Ming-Hsuan Yang 0001. 73-81 [doi]
- On Information Gain and Regret Bounds in Gaussian Process BanditsSattar Vakili, Kia Khezeli, Victor Picheny. 82-90 [doi]
- On the proliferation of support vectors in high dimensionsDaniel Hsu 0001, Vidya Muthukumar, Ji Xu. 91-99 [doi]
- Continual Learning using a Bayesian Nonparametric Dictionary of Weight FactorsNikhil Mehta, Kevin J. Liang, Vinay Kumar Verma, Lawrence Carin. 100-108 [doi]
- A Fast and Robust Method for Global Topological Functional OptimizationYitzchak Solomon, Alexander Wagner, Paul Bendich. 109-117 [doi]
- Regression Discontinuity Design under Self-selectionSida Peng, Yang Ning. 118-126 [doi]
- Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing CampaignsZiping Xu, Amirhossein Meisami, Ambuj Tewari. 127-135 [doi]
- When OT meets MoM: Robust estimation of Wasserstein DistanceGuillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc. 136-144 [doi]
- Learning Individually Fair Classifier with Path-Specific Causal-Effect ConstraintYoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima. 145-153 [doi]
- Unconstrained MAP Inference, Exponentiated Determinantal Point Processes, and Exponential InapproximabilityNaoto Ohsaka. 154-162 [doi]
- False Discovery Rates in Biological NetworksLu Yu, Tobias Kaufmann, Johannes Lederer. 163-171 [doi]
- Fourier Bases for Solving Permutation PuzzlesHorace Pan, Risi Kondor. 172-180 [doi]
- Accelerating Metropolis-Hastings with Lightweight Inference CompilationFeynman T. Liang, Nimar S. Arora, Nazanin Khosravani Tehrani, Yucen Lily Li, Michael Tingley, Erik Meijer 0001. 181-189 [doi]
- Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time SeriesXing Han, Sambarta Dasgupta, Joydeep Ghosh. 190-198 [doi]
- Fully Gap-Dependent Bounds for Multinomial Logit BanditJiaqi Yang. 199-207 [doi]
- Alternating Direction Method of Multipliers for QuantizationTianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn. 208-216 [doi]
- Online Forgetting Process for Linear Regression ModelsYuantong Li, Chi-Hua Wang, Guang Cheng. 217-225 [doi]
- A Bayesian nonparametric approach to count-min sketch under power-law data streamsEmanuele Dolera, Stefano Favaro, Stefano Peluchetti. 226-234 [doi]
- Nonlinear Functional Output Regression: A Dictionary ApproachDimitri Bouche, Marianne Clausel, François Roueff, Florence d'Alché-Buc. 235-243 [doi]
- When MAML Can Adapt Fast and How to Assist When It CannotSébastien M. R. Arnold, Shariq Iqbal, Fei Sha. 244-252 [doi]
- Learning Smooth and Fair RepresentationsXavier Gitiaux, Huzefa Rangwala. 253-261 [doi]
- On Projection Robust Optimal Transport: Sample Complexity and Model MisspecificationTianyi Lin, Zeyu Zheng, Elynn Y. Chen, Marco Cuturi, Michael I. Jordan. 262-270 [doi]
- Contextual Blocking BanditsSoumya Basu 0001, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai. 271-279 [doi]
- Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic ApproximationJia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf. 280-288 [doi]
- A comparative study on sampling with replacement vs Poisson sampling in optimal subsamplingHaiying Wang, Jiahui Zou. 289-297 [doi]
- Robust Imitation Learning from Noisy DemonstrationsVoot Tangkaratt, Nontawat Charoenphakdee, Masashi Sugiyama. 298-306 [doi]
- Online Active Model Selection for Pre-trained ClassifiersMohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang 0001, Andreas Krause 0001. 307-315 [doi]
- Online Sparse Reinforcement LearningBotao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang. 316-324 [doi]
- A Contraction Approach to Model-based Reinforcement LearningTing-Han Fan, Peter J. Ramadge. 325-333 [doi]
- The Spectrum of Fisher Information of Deep Networks Achieving Dynamical IsometryTomohiro Hayase, Ryo Karakida. 334-342 [doi]
- Benchmarking Simulation-Based InferenceJan-Matthis Lueckmann, Jan Boelts, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke. 343-351 [doi]
- Fisher Auto-EncodersKhalil Elkhalil, Ali-Hasan, Jie Ding 0002, Sina Farsiu, Vahid Tarokh. 352-360 [doi]
- Deep Spectral RankingIlkay Yildiz, Jennifer G. Dy, Deniz Erdogmus, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis. 361-369 [doi]
- Tight Regret Bounds for Infinite-armed Linear Contextual BanditsYingkai Li, Yining Wang, Xi Chen, Yuan Zhou 0007. 370-378 [doi]
- On the Absence of Spurious Local Minima in Nonlinear Low-Rank Matrix Recovery ProblemsYingjie Bi, Javad Lavaei. 379-387 [doi]
- Fast Learning in Reproducing Kernel Krein Spaces via Signed MeasuresFanghui Liu, Xiaolin Huang, Yingyi Chen, Johan A. K. Suykens. 388-396 [doi]
- Approximate Message Passing with Spectral Initialization for Generalized Linear ModelsMarco Mondelli, Ramji Venkataramanan. 397-405 [doi]
- Active Learning with Maximum Margin Sparse Gaussian ProcessesWeishi Shi, Qi Yu 0001. 406-414 [doi]
- A Stein Goodness-of-test for Exponential Random Graph ModelsWenkai Xu, Gesine Reinert. 415-423 [doi]
- The Sample Complexity of Level Set ApproximationFrançois Bachoc, Tommaso Cesari, Sébastien Gerchinovitz. 424-432 [doi]
- Curriculum Learning by Optimizing Learning DynamicsTianyi Zhou, Shengjie Wang, Jeff A. Bilmes. 433-441 [doi]
- Approximating Lipschitz continuous functions with GroupSort neural networksUgo Tanielian, Gérard Biau. 442-450 [doi]
- Learning GPLVM with arbitrary kernels using the unscented transformationDaniel de Souza, Diego P. P. Mesquita, João Paulo Pordeus Gomes, César Lincoln C. Mattos. 451-459 [doi]
- Low-Rank Generalized Linear Bandit ProblemsYangyi Lu, Amirhossein Meisami, Ambuj Tewari. 460-468 [doi]
- On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributionsKai Brügge 0001, Asja Fischer, Christian Igel. 469-477 [doi]
- Learning Partially Known Stochastic Dynamics with Empirical PAC BayesManuel Haußmann, Sebastian Gerwinn, Andreas Look, Barbara Rakitsch, Melih Kandemir. 478-486 [doi]
- SONIA: A Symmetric Blockwise Truncated Optimization AlgorithmMajid Jahani, MohammadReza Nazari, Rachael Tappenden, Albert S. Berahas, Martin Takác. 487-495 [doi]
- Predictive Power of Nearest Neighbors Algorithm under Random PerturbationYue Xing, Qifan Song, Guang Cheng. 496-504 [doi]
- On the Generalization Properties of Adversarial TrainingYue Xing, Qifan Song, Guang Cheng. 505-513 [doi]
- Adversarially Robust Estimate and Risk Analysis in Linear RegressionYue Xing, Ruizhi Zhang, Guang Cheng. 514-522 [doi]
- Adaptive Approximate Policy IterationBotao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvári. 523-531 [doi]
- Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and ApplicationsGuillaume Ausset, Stéphan Clémençon, François Portier. 532-540 [doi]
- Foundations of Bayesian Learning from Synthetic DataHarrison Wilde, Jack Jewson, Sebastian J. Vollmer, Chris Holmes. 541-549 [doi]
- Generalization of Quasi-Newton Methods: Application to Robust Symmetric Multisecant UpdatesDamien Scieur, Lewis Liu, Thomas Pumir, Nicolas Boumal. 550-558 [doi]
- Hierarchical Clustering via Sketches and Hierarchical Correlation ClusteringDanny Vainstein, Vaggos Chatziafratis, Gui Citovsky, Anand Rajagopalan, Mohammad Mahdian, Yossi Azar. 559-567 [doi]
- Generalization Bounds for Stochastic Saddle Point ProblemsJunyu Zhang, Mingyi Hong, Mengdi Wang, Shuzhong Zhang. 568-576 [doi]
- Learning to Defend by Learning to AttackHaoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao. 577-585 [doi]
- A Deterministic Streaming Sketch for Ridge RegressionBenwei Shi, Jeff M. Phillips. 586-594 [doi]
- Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical SystemsMansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao. 595-603 [doi]
- On the role of data in PAC-BayesGintare Karolina Dziugaite, Kyle Hsu, Waseem Gharbieh, Gabriel Arpino, Daniel Roy 0001. 604-612 [doi]
- CADA: Communication-Adaptive Distributed AdamTianyi Chen, Ziye Guo, Yuejiao Sun, Wotao Yin. 613-621 [doi]
- Bandit algorithms: Letting go of logarithmic regret for statistical robustnessKumar Ashutosh, Jayakrishnan Nair, Anmol Kagrecha, Krishna P. Jagannathan. 622-630 [doi]
- Geometrically Enriched Latent SpacesGeorgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf. 631-639 [doi]
- Confident Off-Policy Evaluation and Selection through Self-Normalized Importance WeightingIlja Kuzborskij, Claire Vernade, András György 0001, Csaba Szepesvári. 640-648 [doi]
- Kernel regression in high dimensions: Refined analysis beyond double descentFanghui Liu, Zhenyu Liao, Johan A. K. Suykens. 649-657 [doi]
- Self-Concordant Analysis of Generalized Linear Bandits with ForgettingYoan Russac, Louis Faury, Olivier Cappé, Aurélien Garivier. 658-666 [doi]
- Logical Team Q-learning: An approach towards factored policies in cooperative MARLLucas Cassano, Ali H. Sayed. 667-675 [doi]
- Automatic structured variational inferenceLuca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven. 676-684 [doi]
- Neural Enhanced Belief Propagation on Factor GraphsVictor Garcia Satorras, Max Welling. 685-693 [doi]
- Predictive Complexity PriorsEric T. Nalisnick, Jonathan Gordon 0003, José Miguel Hernández-Lobato. 694-702 [doi]
- Improving predictions of Bayesian neural nets via local linearizationAlexander Immer, Maciej Korzepa, Matthias Bauer. 703-711 [doi]
- Generalized Spectral Clustering via Gromov-Wasserstein LearningSamir Chowdhury 0001, Tom Needham. 712-720 [doi]
- Shapley Flow: A Graph-based Approach to Interpreting Model PredictionsJiaxuan Wang, Jenna Wiens, Scott Lundberg. 721-729 [doi]
- Scalable Constrained Bayesian OptimizationDavid Eriksson, Matthias Poloczek. 730-738 [doi]
- Sample efficient learning of image-based diagnostic classifiers via probabilistic labelsRoberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth Hareendranathan, Jeevesh Kapur, Jacob L. Jaremko, Russell Greiner. 739-747 [doi]
- Nonparametric Variable Screening with Optimal Decision StumpsJason M. Klusowski, Peter M. Tian. 748-756 [doi]
- Sharp Analysis of a Simple Model for Random ForestsJason M. Klusowski. 757-765 [doi]
- Nested Barycentric Coordinate System as an Explicit Feature MapLee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele. 766-774 [doi]
- An Analysis of the Adaptation Speed of Causal ModelsRémi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien. 775-783 [doi]
- Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness ConstraintsRobin Vogel, Aurélien Bellet, Stéphan Clémençon. 784-792 [doi]
- Efficient Computation and Analysis of Distributional Shapley ValuesYongchan Kwon, Manuel A. Rivas, James Zou. 793-801 [doi]
- A constrained risk inequality for general lossesJohn C. Duchi, Feng Ruan. 802-810 [doi]
- Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning AlgorithmsTengyu Xu, Yingbin Liang. 811-819 [doi]
- Learning Prediction Intervals for Regression: Generalization and CalibrationHaoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang. 820-828 [doi]
- Regularization Matters: A Nonparametric Perspective on Overparametrized Neural NetworkTianyang Hu, Wenjia Wang, Cong Lin, Guang Cheng. 829-837 [doi]
- Revisiting Model-Agnostic Private Learning: Faster Rates and Active LearningChong Liu, Yuqing Zhu 0005, Kamalika Chaudhuri, Yu-Xiang Wang. 838-846 [doi]
- Multi-Fidelity High-Order Gaussian Processes for Physical SimulationZheng Wang, Wei Xing, Robert Michael Kirby, Shandian Zhe. 847-855 [doi]
- Deep Fourier Kernel for Self-Attentive Point ProcessesShixiang Zhu, Minghe Zhang, Ruyi Ding, Yao Xie 0002. 856-864 [doi]
- Robustness and scalability under heavy tails, without strong convexityMatthew Holland. 865-873 [doi]
- Understanding the wiring evolution in differentiable neural architecture searchSirui Xie, Shoukang Hu, Xinjiang Wang, Chunxiao Liu, Jianping Shi, Xunying Liu, Dahua Lin. 874-882 [doi]
- Provable Hierarchical Imitation Learning via EMZhiyu Zhang, Ioannis Ch. Paschalidis. 883-891 [doi]
- Learning with risk-averse feedback under potentially heavy tailsMatthew J. Holland, El Mehdi Haress. 892-900 [doi]
- Parametric Programming Approach for More Powerful and General Lasso Selective InferenceVo Nguyen Le Duy, Ichiro Takeuchi. 901-909 [doi]
- On the High Accuracy Limitation of Adaptive Property EstimationYanjun Han. 910-918 [doi]
- Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across LayersAlex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio. 919-927 [doi]
- Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce ModelJiaqi Ma 0001, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed Chi, Qiaozhu Mei. 928-936 [doi]
- Interpretable Random Forests via Rule ExtractionClément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet. 937-945 [doi]
- Regret Minimization for Causal Inference on Large Treatment SpaceAkira Tanimoto, Tomoya Sakai 0001, Takashi Takenouchi, Hisashi Kashima. 946-954 [doi]
- Bayesian Model Averaging for Causality Estimation and its Approximation based on Gaussian Scale Mixture DistributionsShunsuke Horii. 955-963 [doi]
- Adaptive Sampling for Fast Constrained Maximization of Submodular FunctionsFrancesco Quinzan, Vanja Doskoc, Andreas Göbel 0001, Tobias Friedrich 0001. 964-972 [doi]
- Mean-Variance Analysis in Bayesian Optimization under UncertaintyShogo Iwazaki, Yu Inatsu, Ichiro Takeuchi. 973-981 [doi]
- Hadamard Wirtinger Flow for Sparse Phase RetrievalFan Wu, Patrick Rebeschini. 982-990 [doi]
- Stochastic Linear Bandits Robust to Adversarial AttacksIlija Bogunovic, Arpan Losalka, Andreas Krause 0001, Jonathan Scarlett. 991-999 [doi]
- ATOL: Measure Vectorization for Automatic Topologically-Oriented LearningMartin Royer, Frédéric Chazal, Clément Levrard, Yuhei Umeda, Yuichi Ike. 1000-1008 [doi]
- Optimizing Percentile Criterion using Robust MDPsBahram Behzadian, Reazul Hasan Russel, Marek Petrik, Chin Pang Ho. 1009-1017 [doi]
- On Riemannian Stochastic Approximation Schemes with Fixed Step-SizeAlain Durmus, Pablo Jiménez, Eric Moulines, Salem Said. 1018-1026 [doi]
- Optimal Quantisation of Probability Measures Using Maximum Mean DiscrepancyOnur Teymur, Jackson Gorham, Marina Riabiz, Chris J. Oates. 1027-1035 [doi]
- Aligning Time Series on Incomparable SpacesSamuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth. 1036-1044 [doi]
- The Unexpected Deterministic and Universal Behavior of Large Softmax ClassifiersMohamed-El-Amine Seddik, Cosme Louart, Romain Couillet, Mohamed Tamaazousti. 1045-1053 [doi]
- Measure Transport with Kernel Stein DiscrepancyMatthew Fisher, Tui Nolan, Matthew Graham, Dennis Prangle, Chris Oates. 1054-1062 [doi]
- Unifying Clustered and Non-stationary BanditsChuanhao Li, Qingyun Wu, Hongning Wang. 1063-1071 [doi]
- A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap MatrixThang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier. 1072-1080 [doi]
- Transforming Gaussian Processes With Normalizing FlowsJuan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas. 1081-1089 [doi]
- Linearly Constrained Gaussian Processes with Boundary ConditionsMarkus Lange-Hegermann. 1090-1098 [doi]
- Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean EmbeddingsJean-Francois Ton, Lucian Chan, Yee Whye Teh, Dino Sejdinovic. 1099-1107 [doi]
- Top-m identification for linear banditsClémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez. 1108-1116 [doi]
- When Will Generative Adversarial Imitation Learning Algorithms Attain Global ConvergenceZiwei Guan, Tengyu Xu, Yingbin Liang. 1117-1125 [doi]
- Online k-means ClusteringVincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom. 1126-1134 [doi]
- Consistent k-Median: Simpler, Better and RobustXiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian. 1135-1143 [doi]
- Algorithms for Fairness in Sequential Decision MakingMin Wen, Osbert Bastani, Ufuk Topcu. 1144-1152 [doi]
- On Learning Continuous Pairwise Markov Random FieldsAbhin Shah, Devavrat Shah, Gregory W. Wornell. 1153-1161 [doi]
- Abstract Value Iteration for Hierarchical Reinforcement LearningKishor Jothimurugan, Osbert Bastani, Rajeev Alur. 1162-1170 [doi]
- Differentially Private Analysis on Graph StreamsJalaj Upadhyay, Sarvagya Upadhyay, Raman Arora. 1171-1179 [doi]
- Learning with Hyperspherical UniformityWeiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong 0001, Bernhard Schölkopf, Adrian Weller. 1180-1188 [doi]
- Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda FunctionIoannis C. Tsaknakis, Mingyi Hong. 1189-1197 [doi]
- Latent Derivative Bayesian Last Layer NetworksJoe Watson, Jihao Andreas Lin, Pascal Klink, Joni Pajarinen, Jan Peters 0001. 1198-1206 [doi]
- Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch SizesNhuong V. Nguyen, Toan N. Nguyen, Phuong Ha Nguyen, Quoc Tran-Dinh, Lam M. Nguyen, Marten van Dijk. 1207-1215 [doi]
- Provably Safe PAC-MDP Exploration Using AnalogiesMelrose Roderick, Vaishnavh Nagarajan, J. Zico Kolter. 1216-1224 [doi]
- Maximal Couplings of the Metropolis-Hastings AlgorithmGuanyang Wang, John O'Leary, Pierre Jacob. 1225-1233 [doi]
- Gaming Helps! Learning from Strategic Interactions in Natural DynamicsYahav Bechavod, Katrina Ligett, Zhiwei Steven Wu, Juba Ziani. 1234-1242 [doi]
- Goodness-of-Fit Test for Mismatched Self-Exciting ProcessesSong Wei, Shixiang Zhu, Minghe Zhang, Yao Xie 0002. 1243-1251 [doi]
- Dominate or Delete: Decentralized Competing Bandits in Serial DictatorshipAbishek Sankararaman, Soumya Basu 0001, Karthik Abinav Sankararaman. 1252-1260 [doi]
- A Study of Condition Numbers for First-Order OptimizationCharles Guille-Escuret, Manuela Girotti, Baptiste Goujaud, Ioannis Mitliagkas. 1261-1269 [doi]
- Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution SolutionsKartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar. 1270-1278 [doi]
- Differentially Private Online Submodular MaximizationSebastian Perez-Salazar, Rachel Cummings. 1279-1287 [doi]
- Anderson acceleration of coordinate descentQuentin Bertrand, Mathurin Massias. 1288-1296 [doi]
- Inference in Stochastic Epidemic Models via Multinomial ApproximationsNick Whiteley, Lorenzo Rimella. 1297-1305 [doi]
- Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast ConvergenceNicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien. 1306-1314 [doi]
- SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and InterpolationRobert M. Gower, Othmane Sebbouh, Nicolas Loizou. 1315-1323 [doi]
- Stable ResNetSoufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau. 1324-1332 [doi]
- Latent variable modeling with random featuresGregory W. Gundersen, Michael Zhang, Barbara E. Engelhardt. 1333-1341 [doi]
- Reaping the Benefits of Bundling under High Production CostsWill Ma, David Simchi-Levi. 1342-1350 [doi]
- Momentum Improves Optimization on Riemannian ManifoldsFoivos Alimisis, Antonio Orvieto, Gary Bécigneul, Aurélien Lucchi. 1351-1359 [doi]
- Quick Streaming Algorithms for Maximization of Monotone Submodular Functions in Linear TimeAlan Kuhnle. 1360-1368 [doi]
- On Data Efficiency of Meta-learningMaruan Al-Shedivat, Liam Li, Eric P. Xing, Ameet Talwalkar. 1369-1377 [doi]
- Hyperparameter Transfer Learning with Adaptive ComplexitySamuel Horváth, Aaron Klein, Peter Richtárik, Cédric Archambeau. 1378-1386 [doi]
- Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication EfficiencyYuyang Deng, Mehrdad Mahdavi. 1387-1395 [doi]
- Problem-Complexity Adaptive Model Selection for Stochastic Linear BanditsAvishek Ghosh, Abishek Sankararaman, Kannan Ramchandran. 1396-1404 [doi]
- On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear RegressionJeongyeol Kwon, Nhat Ho, Constantine Caramanis. 1405-1413 [doi]
- Amortized Bayesian Prototype Meta-learning: A New Probabilistic Meta-learning Approach to Few-shot Image ClassificationZhuo Sun, Jijie Wu, Xiaoxu Li, Wenming Yang, Jing-Hao Xue. 1414-1422 [doi]
- Tractable contextual bandits beyond realizabilitySanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey. 1423-1431 [doi]
- Learning User Preferences in Non-Stationary EnvironmentsWasim Huleihel, Soumyabrata Pal, Ofer Shayevitz. 1432-1440 [doi]
- Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapesQi Lei, Sai Ganesh Nagarajan, Ioannis Panageas, Xiao Wang. 1441-1449 [doi]
- Efficient Statistics for Sparse Graphical Models from Truncated SamplesArnab Bhattacharyya 0001, Rathin Desai, Sai Ganesh Nagarajan, Ioannis Panageas. 1450-1458 [doi]
- Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their InterpretationsNeil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath. 1459-1467 [doi]
- Feedback Coding for Active LearningGregory Canal, Matthieu Bloch, Christopher Rozell. 1468-1476 [doi]
- Shadow Manifold Hamiltonian Monte CarloChristopher van der Heide, Fred Roosta, Liam Hodgkinson, Dirk Kroese. 1477-1485 [doi]
- Towards Understanding the Behaviors of Optimal Deep Active Learning AlgorithmsYilun Zhou, Adithya Renduchintala, Xian Li, Sida Wang, Yashar Mehdad, Asish Ghoshal. 1486-1494 [doi]
- Identification of Matrix Joint Block DiagonalizationYunfeng Cai, Ping Li. 1495-1503 [doi]
- Understanding Gradient Clipping In Incremental Gradient MethodsJiang Qian, Yuren Wu, BoJin Zhuang, Shaojun Wang, Jing Xiao. 1504-1512 [doi]
- A Variational Information Bottleneck Approach to Multi-Omics Data IntegrationChangHee Lee, Mihaela van der Schaar. 1513-1521 [doi]
- On the Privacy Properties of GAN-generated SamplesZinan Lin 0001, Vyas Sekar, Giulia C. Fanti. 1522-1530 [doi]
- Multitask Bandit Learning Through Heterogeneous Feedback AggregationZhi Wang, Chicheng Zhang, Manish Kumar Singh, Laurel D. Riek, Kamalika Chaudhuri. 1531-1539 [doi]
- Learning Complexity of Simulated AnnealingAvrim Blum, Chen Dan 0001, Saeed Seddighin. 1540-1548 [doi]
- Independent Innovation Analysis for Nonlinear Vector Autoregressive ProcessHiroshi Morioka, Hermanni Hälvä, Aapo Hyvärinen. 1549-1557 [doi]
- Robust Mean Estimation on Highly Incomplete Data with Arbitrary OutliersLunjia Hu, Omer Reingold. 1558-1566 [doi]
- Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement LearningMing Yin, Yu Bai, Yu-Xiang Wang. 1567-1575 [doi]
- Q-learning with Logarithmic RegretKunhe Yang, Lin F. Yang, Simon S. Du. 1576-1584 [doi]
- An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson SamplingQin Ding 0002, Cho-Jui Hsieh, James Sharpnack. 1585-1593 [doi]
- Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed OptimizationCongliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhi-Quan Luo. 1594-1602 [doi]
- Robust and Private Learning of HalfspacesBadih Ghazi, Ravi Kumar 0001, Pasin Manurangsi, Thao Nguyen. 1603-1611 [doi]
- Minimax Model LearningCameron Voloshin, Nan Jiang, Yisong Yue. 1612-1620 [doi]
- On the Faster Alternating Least-Squares for CCAZhiqiang Xu, Ping Li 0001. 1621-1629 [doi]
- Exploiting Equality Constraints in Causal InferenceChi Zhang 0016, Carlos Cinelli, Bryant Chen, Judea Pearl. 1630-1638 [doi]
- Collaborative Classification from Noisy LabelsLucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas. 1639-1647 [doi]
- Fenchel-Young Losses with Skewed Entropies for Class-posterior Probability EstimationHan Bao 0002, Masashi Sugiyama. 1648-1656 [doi]
- Maximizing Agreements for Ranking, Clustering and Hierarchical Clustering via MAX-CUTVaggos Chatziafratis, Mohammad Mahdian, Sara Ahmadian. 1657-1665 [doi]
- Why did the distribution change?Kailash Budhathoki, Dominik Janzing, Patrick Blöbaum, Hoiyi Ng. 1666-1674 [doi]
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