Table of Contents

• Cross-Loss Influence Functions to Explain Deep Network RepresentationsAndrew Silva, Rohit Chopra, Matthew C. Gombolay. 1-17 [doi]
• Federated Reinforcement Learning with Environment HeterogeneityHao Jin, Yang Peng, Wenhao Yang, Shusen Wang, Zhihua Zhang. 18-37 [doi]
• On Linear Model with Markov Signal PriorsLan V. Truong. 38-53 [doi]
• Maillard Sampling: Boltzmann Exploration Done OptimallyJie Bian, Kwang-Sung Jun. 54-72 [doi]
• Norm-Agnostic Linear BanditsSpencer B. Gales, Sunder Sethuraman, Kwang-Sung Jun. 73-91 [doi]
• Gaussian Process Bandit Optimization with Few BatchesZihan Li, Jonathan Scarlett. 92-107 [doi]
• Approximate Function Evaluation via Multi-Armed BanditsTavor Z. Baharav, Gary Cheng 0004, Mert Pilanci, David Tse. 108-135 [doi]
• Unlabeled Data Help: Minimax Analysis and Adversarial RobustnessYue Xing, Qifan Song, Guang Cheng. 136-168 [doi]
• System-Agnostic Meta-Learning for MDP-based Dynamic Scheduling via Descriptive PolicyHyun Suk Lee. 169-187 [doi]
• Deep Layer-wise Networks Have Closed-Form WeightsChieh Tzu Wu, Aria Masoomi, Arthur Gretton, Jennifer G. Dy. 188-225 [doi]
• Sequential Multivariate Change Detection with Calibrated and Memoryless False Detection RatesOliver Cobb, Arnaud Van Looveren, Janis Klaise. 226-239 [doi]
• Neural Contextual Bandits without RegretParnian Kassraie, Andreas Krause 0001. 240-278 [doi]
• SAN: Stochastic Average Newton Algorithm for Minimizing Finite SumsJiabin Chen, Rui Yuan, Guillaume Garrigos, Robert M. Gower. 279-318 [doi]
• Factorization Approach for Low-complexity Matrix Completion Problems: Exponential Number of Spurious Solutions and Failure of Gradient MethodsBaturalp Yalcin, Haixiang Zhang, Javad Lavaei, Somayeh Sojoudi. 319-341 [doi]
• k-experts - Online Policies and Fundamental LimitsSamrat Mukhopadhyay, Sourav Sahoo 0001, Abhishek Sinha. 342-365 [doi]
• Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With CocoercivityEduard Gorbunov, Nicolas Loizou, Gauthier Gidel. 366-402 [doi]
• Multi-armed Bandit Algorithm against Strategic ReplicationSuho Shin, Seungjoon Lee, Jungseul Ok. 403-431 [doi]
• Gap-Dependent Bounds for Two-Player Markov GamesZehao Dou, Zhuoran Yang, Zhaoran Wang, Simon S. Du. 432-455 [doi]
• Exploiting Correlation to Achieve Faster Learning Rates in Low-Rank Preference BanditsAadirupa Saha, Suprovat Ghoshal. 456-482 [doi]
• Exploring Image Regions Not Well Encoded by an INNZenan Ling, Fan Zhou, Meng Wei, Quanshi Zhang. 483-509 [doi]
• Finding Dynamics Preserving Adversarial Winning TicketsXupeng Shi, Pengfei Zheng, A. Adam Ding, Yuan Gao, Weizhong Zhang. 510-528 [doi]
• Being a Bit Frequentist Improves Bayesian Neural NetworksAgustinus Kristiadi, Matthias Hein 0001, Philipp Hennig. 529-545 [doi]
• Jointly Efficient and Optimal Algorithms for Logistic BanditsLouis Faury, Marc Abeille, Kwang-Sung Jun, Clément Calauzènes. 546-580 [doi]
• Obtaining Causal Information by Merging Datasets with MAXENTSergio H. Garrido Mejia, Elke Kirschbaum, Dominik Janzing. 581-603 [doi]
• Distributed Sparse Multicategory Discriminant AnalysisHengchao Chen, Qiang Sun. 604-624 [doi]
• Probabilistic Numerical Method of Lines for Time-Dependent Partial Differential EquationsNicholas Krämer, Jonathan Schmidt, Philipp Hennig. 625-639 [doi]
• A View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares HierarchyKevin Bello, Chuyang Ke, Jean Honorio. 640-654 [doi]
• Marginalized Operators for Off-policy Reinforcement LearningYunhao Tang, Mark Rowland, Remi Munos, Michal Valko. 655-679 [doi]
• Basis Matters: Better Communication-Efficient Second Order Methods for Federated LearningXun Qian, Rustem Islamov, Mher Safaryan, Peter Richtárik. 680-720 [doi]
• Infinitely Deep Bayesian Neural Networks with Stochastic Differential EquationsWinnie Xu, Ricky T. Q. Chen, Xuechen Li, David Duvenaud. 721-738 [doi]
• Causally motivated shortcut removal using auxiliary labelsMaggie Makar, Ben Packer, Dan Moldovan, Davis Blalock, Yoni Halpern, Alexander D'Amour. 739-766 [doi]
• Learning to Plan Variable Length Sequences of Actions with a Cascading Bandit Click Model of User FeedbackAnirban Santara, Gaurav Aggarwal, Shuai Li, Claudio Gentile. 767-797 [doi]
• Identity Testing of Reversible Markov ChainsSela Fried, Geoffrey Wolfer. 798-817 [doi]
• Sampling in Dirichlet Process Mixture Models for Clustering Streaming DataOr Dinari, Oren Freifeld. 818-835 [doi]
• A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement LearningYoussef Diouane, Aurélien Lucchi, Vihang Prakash Patil. 836-859 [doi]
• Adaptively Partitioning Max-Affine Estimators for Convex RegressionGábor Balázs. 860-874 [doi]
• Variational Marginal Particle FiltersJinlin Lai, Justin Domke, Daniel Sheldon. 875-895 [doi]
• On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order AlgorithmsNhat Ho, Tianyi Lin, Michael I. Jordan. 896-921 [doi]
• Robustness and Reliability When Training With Noisy LabelsAmanda Olmin, Fredrik Lindsten. 922-942 [doi]
• Robust Bayesian Inference for Simulator-based Models via the MMD Posterior BootstrapCharita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol. 943-970 [doi]
• A Last Switch Dependent Analysis of Satiation and Seasonality in BanditsPierre Laforgue, Giulia Clerici, Nicolò Cesa-Bianchi, Ran Gilad-Bachrach. 971-990 [doi]
• Analysis of a Target-Based Actor-Critic Algorithm with Linear Function ApproximationAnas Barakat, Pascal Bianchi, Julien Lehmann. 991-1040 [doi]
• Policy Learning and Evaluation with Randomized Quasi-Monte CarloSébastien M. R. Arnold, Pierre L'Ecuyer, Liyu Chen, Yi-Fan Chen, Fei Sha. 1041-1061 [doi]
• Learning Personalized Item-to-Item Recommendation Metric via Implicit FeedbackTrong Nghia Hoang, Anoop Deoras, Tong Zhao, Jin Li 0003, George Karypis. 1062-1077 [doi]
• Multiway Spherical Clustering via Degree-Corrected Tensor Block ModelsJiaxin Hu, Miaoyan Wang. 1078-1119 [doi]
• Fixed Support Tree-Sliced Wasserstein BarycenterYuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada. 1120-1137 [doi]
• k-Pareto Optimality-Based Sorting with Maximization of ChoiceJean Ruppert, Marharyta Aleksandrova, Thomas Engel 0001. 1138-1160 [doi]
• Towards Return Parity in Markov Decision ProcessesJianfeng Chi, Jian Shen, Xinyi Dai, Weinan Zhang 0001, Yuan Tian 0001, Han Zhao 0002. 1161-1178 [doi]
• Uncertainty Quantification for Low-Rank Matrix Completion with Heterogeneous and Sub-Exponential NoiseVivek F. Farias, Andrew A. Li, Tianyi Peng. 1179-1189 [doi]
• Survival regression with proper scoring rules and monotonic neural networksDavid Rindt, Robert Hu, David Steinsaltz, Dino Sejdinovic. 1190-1205 [doi]
• Physics Informed Deep Kernel LearningZheng Wang, Wei Xing, Robert M. Kirby, Shandian Zhe. 1206-1218 [doi]
• Fast Distributionally Robust Learning with Variance-Reduced Min-Max OptimizationYaodong Yu, Tianyi Lin, Eric V. Mazumdar, Michael I. Jordan. 1219-1250 [doi]
• Heavy-tailed Streaming Statistical EstimationChe-Ping Tsai, Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar. 1251-1282 [doi]
• On Distributionally Robust Optimization and Data RebalancingAgnieszka Slowik, Léon Bottou. 1283-1297 [doi]
• Spiked Covariance Estimation from Modulo-Reduced MeasurementsElad Romanov, Or Ordentlich. 1298-1320 [doi]
• A Contraction Theory Approach to Optimization Algorithms from Acceleration FlowsPedro Cisneros-Velarde, Francesco Bullo. 1321-1335 [doi]
• Robust Probabilistic Time Series ForecastingTaeho Yoon, Youngsuk Park, Ernest K. Ryu, Yuyang Wang. 1336-1358 [doi]
• VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity RecognitionRandy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian. 1359-1379 [doi]
• Implicitly Regularized RL with Implicit Q-valuesNino Vieillard, Marcin Andrychowicz, Anton Raichuk, Olivier Pietquin, Matthieu Geist. 1380-1402 [doi]
• A Witness Two-Sample TestJonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet. 1403-1419 [doi]
• Sample-and-threshold differential privacy: Histograms and applicationsGraham Cormode, Akash Bharadwaj. 1420-1431 [doi]
• Common Failure Modes of Subcluster-based Sampling in Dirichlet Process Gaussian Mixture Models - and a Deep-learning SolutionVlad Winter, Or Dinari, Oren Freifeld. 1432-1456 [doi]
• A Complete Characterisation of ReLU-Invariant DistributionsJan MacDonald, Stephan Wäldchen. 1457-1484 [doi]
• Threading the Needle of On and Off-Manifold Value Functions for Shapley ExplanationsChih-Kuan Yeh, Kuan-Yun Lee, Frederick Liu, Pradeep Ravikumar. 1485-1502 [doi]
• Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian InferenceLuca Rendsburg, Agustinus Kristiadi, Philipp Hennig, Ulrike von Luxburg. 1503-1526 [doi]
• Equivariance Discovery by Learned Parameter-SharingRaymond A. Yeh, Yuan-Ting Hu, Mark Hasegawa-Johnson, Alexander G. Schwing. 1527-1545 [doi]
• Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed BanditsYouming Tao, Yulian Wu, Peng Zhao, Di Wang. 1546-1574 [doi]
• Standardisation-function Kernel Stein Discrepancy: A Unifying View on Kernel Stein Discrepancy Tests for Goodness-of-fitWenkai Xu. 1575-1597 [doi]
• Parametric Bootstrap for Differentially Private Confidence IntervalsCecilia Ferrando, Shufan Wang, Daniel Sheldon. 1598-1618 [doi]
• Nearly Tight Convergence Bounds for Semi-discrete Entropic Optimal TransportAlex Delalande. 1619-1642 [doi]
• Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly DetectionCristian I. Challu, Peihong Jiang, Ying Nian Wu, Laurent Callot. 1643-1654 [doi]
• Online Page Migration with ML AdvicePiotr Indyk, Frederik Mallmann-Trenn, Slobodan Mitrovic, Ronitt Rubinfeld. 1655-1670 [doi]
• Policy Learning for Optimal Individualized Dose IntervalsGuanhua Chen, Xiaomao Li, Menggang Yu. 1671-1693 [doi]
• Deep Multi-Fidelity Active Learning of High-Dimensional OutputsShibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe. 1694-1711 [doi]
• Online Learning for Unknown Partially Observable MDPsMehdi Jafarnia-Jahromi, Rahul Jain 0002, Ashutosh Nayyar. 1712-1732 [doi]
• Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably?Lisha Chen, Tianyi Chen. 1733-1774 [doi]
• A Bayesian Model for Online Activity Sample SizesThomas S. Richardson, Yu Liu, James McQueen, Doug Hains. 1775-1785 [doi]
• Parallel MCMC Without Embarrassing FailuresDaniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi. 1786-1804 [doi]
• Optimal Dynamic Regret in Proper Online Learning with Strongly Convex Losses and BeyondDheeraj Baby, Yu-Xiang Wang 0003. 1805-1845 [doi]
• Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision TreesKentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike. 1846-1870 [doi]
• Spectral risk-based learning using unbounded lossesMatthew J. Holland, El Mehdi Haress. 1871-1886 [doi]
• A Dual Approach to Constrained Markov Decision Processes with Entropy RegularizationDonghao Ying, Yuhao Ding, Javad Lavaei. 1887-1909 [doi]
• On the Global Optimum Convergence of Momentum-based Policy GradientYuhao Ding, Junzi Zhang, Javad Lavaei. 1910-1934 [doi]
• Feature screening with kernel knockoffsBenjamin Poignard, Peter J. Naylor, Héctor Climente-González, Makoto Yamada. 1935-1974 [doi]
• Bias-Variance Decompositions for Margin LossesDanny Wood, Tingting Mu, Gavin Brown 0001. 1975-2001 [doi]
• Grassmann Stein Variational Gradient DescentXing Liu, Harrison Zhu, Jean-Francois Ton, George Wynne, Andrew Duncan. 2002-2021 [doi]
• Nonstochastic Bandits and Experts with Arm-Dependent DelaysDirk van der Hoeven, Nicolò Cesa-Bianchi. 2022-2044 [doi]
• Improved analysis of randomized SVD for top-eigenvector approximationRuo-Chun Tzeng, Po-An Wang, Florian Adriaens, Aristides Gionis, Chi-Jen Lu. 2045-2072 [doi]
• p-Generalized Probit Regression and Scalable Maximum Likelihood Estimation via Sketching and CoresetsAlexander Munteanu, Simon Omlor, Christian Peters. 2073-2100 [doi]
• Non-stationary Online Learning with Memory and Non-stochastic ControlPeng Zhao 0006, Yu-Xiang Wang 0003, Zhi-Hua Zhou. 2101-2133 [doi]
• Dimensionality Reduction and Prioritized Exploration for Policy SearchMarius Memmel, Puze Liu, Davide Tateo, Jan Peters 0001. 2134-2157 [doi]
• The Curse Revisited: When are Distances Informative for the Ground Truth in Noisy High-Dimensional Data?Robin Vandaele, Bo Kang, Tijl De Bie, Yvan Saeys. 2158-2172 [doi]
• Improving Attribution Methods by Learning Submodular FunctionsPiyushi Manupriya, Tarun Ram Menta, Sakethanath Nath Jagarlapudi, Vineeth N. Balasubramanian. 2173-2190 [doi]
• Conditional Gradients for the Approximately Vanishing IdealElias Samuel Wirth, Sebastian Pokutta. 2191-2209 [doi]
• Efficient Algorithms for Extreme BanditsDorian Baudry, Yoan Russac, Emilie Kaufmann. 2210-2248 [doi]
• Rejection sampling from shape-constrained distributions in sublinear timeSinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet. 2249-2265 [doi]
• Learning Inconsistent Preferences with Gaussian ProcessesSiu Lun Chau, Javier González, Dino Sejdinovic. 2266-2281 [doi]
• Bayesian Classifier Fusion with an Explicit Model of CorrelationSusanne Trick, Constantin A. Rothkopf. 2282-2310 [doi]
• Conditionally Gaussian PAC-BayesEugenio Clerico, George Deligiannidis, Arnaud Doucet. 2311-2329 [doi]
• Leveraging Time Irreversibility with Order-Contrastive Pre-trainingMonica N. Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David A. Sontag. 2330-2353 [doi]
• Moment Matching Deep Contrastive Latent Variable ModelsEthan Weinberger, Nicasia Beebe-Wang, Su-In Lee. 2354-2371 [doi]
• Unifying Importance Based Regularisation Methods for Continual LearningFrederik Benzing. 2372-2396 [doi]
• Differentially Private Histograms under Continual Observation: Streaming Selection into the UnknownAdrian Rivera Cardoso, Ryan Rogers 0002. 2397-2419 [doi]
• Confident Least Square Value Iteration with Local Access to a SimulatorBotao Hao, Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvári. 2420-2435 [doi]
• Safe Optimal Design with Applications in Off-Policy LearningRuihao Zhu, Branislav Kveton. 2436-2447 [doi]
• Accurate Shapley Values for explaining tree-based modelsSalim I. Amoukou, Tangi Salaün, Nicolas J.-B. Brunel. 2448-2465 [doi]
• A Single-Timescale Method for Stochastic Bilevel OptimizationTianyi Chen, Yuejiao Sun, Quan Xiao, Wotao Yin. 2466-2488 [doi]
• Strategic rankingLydia T. Liu, Nikhil Garg, Christian Borgs. 2489-2518 [doi]
• Encrypted Linear Contextual BanditEvrard Garcelon, Matteo Pirotta, Vianney Perchet. 2519-2551 [doi]
• Density Ratio Estimation via Infinitesimal ClassificationKristy Choi, Chenlin Meng, Yang Song 0011, Stefano Ermon. 2552-2573 [doi]
• AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep LearningJihun Yun, Aurélie C. Lozano, Eunho Yang. 2574-2606 [doi]
• Scaling and Scalability: Provable Nonconvex Low-Rank Tensor CompletionTian Tong, Cong Ma, Ashley Prater-Bennette, Erin Tripp, Yuejie Chi. 2607-2617 [doi]
• Pairwise Supervision Can Provably Elicit a Decision BoundaryHan Bao 0002, Takuya Shimada, Liyuan Xu, Issei Sato, Masashi Sugiyama. 2618-2640 [doi]
• An Online Learning Approach to Interpolation and Extrapolation in Domain GeneralizationElan Rosenfeld, Pradeep Ravikumar, Andrej Risteski. 2641-2657 [doi]
• On the Convergence Rate of Off-Policy Policy Optimization Methods with Density-Ratio CorrectionJiawei Huang, Nan Jiang. 2658-2705 [doi]
• Loss as the Inconsistency of a Probabilistic Dependency Graph: Choose Your Model, Not Your Loss FunctionOliver E. Richardson. 2706-2735 [doi]
• Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov GamesYulai Zhao, Yuandong Tian, Jason D. Lee, Simon S. Du. 2736-2761 [doi]
• One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and LimitationHajime Ono, Kazuhiro Minami, Hideitsu Hino. 2762-2783 [doi]
• Noise Regularizes Over-parameterized Rank One Matrix Recovery, ProvablyTianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao. 2784-2802 [doi]
• Robust Deep Learning from Crowds with Belief PropagationHoyoung Kim, Seunghyuk Cho, Dongwoo Kim, Jungseul Ok. 2803-2822 [doi]
• Sampling from Arbitrary Functions via PSD ModelsUlysse Marteau-Ferey, Francis Bach, Alessandro Rudi. 2823-2861 [doi]
• Uncertainty Quantification for Bayesian OptimizationRui Tuo, Wenjia Wang. 2862-2884 [doi]
• Metalearning Linear Bandits by Prior UpdateAmit Peleg, Naama Pearl, Ron Meir. 2885-2926 [doi]
• Fast Rank-1 NMF for Missing Data with KL DivergenceKazu Ghalamkari, Mahito Sugiyama. 2927-2940 [doi]
• Randomized Stochastic Gradient Descent AscentOthmane Sebbouh, Marco Cuturi, Gabriel Peyré. 2941-2969 [doi]
• Aligned Multi-Task Gaussian ProcessOlga Mikheeva, Ieva Kazlauskaite, Adam Hartshorne, Hedvig Kjellström, Carl Henrik Ek, Neill D. F. Campbell. 2970-2988 [doi]
• Generative Models as Distributions of FunctionsEmilien Dupont, Yee Whye Teh, Arnaud Doucet. 2989-3015 [doi]
• ContextGen: Targeted Data Generation for Low Resource Domain Specific Text ClassificationLukas Fromme, Jasmina Bogojeska, Jonas Kuhn. 3016-3027 [doi]
• Super-Acceleration with Cyclical Step-sizesBaptiste Goujaud, Damien Scieur, Aymeric Dieuleveut, Adrien B. Taylor, Fabian Pedregosa. 3028-3065 [doi]
• On PAC-Bayesian reconstruction guarantees for VAEsBadr-Eddine Chérief-Abdellatif, Yuyang Shi 0002, Arnaud Doucet, Benjamin Guedj. 3066-3079 [doi]
• MT3: Meta Test-Time Training for Self-Supervised Test-Time AdaptionAlexander Bartler, Andre Bühler, Felix Wiewel, Mario Döbler, Bin Yang 0009. 3080-3090 [doi]
• Random Effect BanditsRong Zhu, Branislav Kveton. 3091-3107 [doi]
• DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor SearchMatti Karppa, Martin Aumüller 0001, Rasmus Pagh. 3108-3137 [doi]
• Embedded Ensembles: infinite width limit and operating regimesMaksim Velikanov, Roman V. Kail, Ivan Anokhin, Roman Vashurin, Maxim Panov, Alexey Zaytsev 0002, Dmitry Yarotsky. 3138-3163 [doi]
• State Dependent Performative Prediction with Stochastic ApproximationQiang Li 0017, Hoi-To Wai. 3164-3186 [doi]
• Reward-Free Policy Space Compression for Reinforcement LearningMirco Mutti, Stefano Del Col, Marcello Restelli. 3187-3203 [doi]
• Nonstationary multi-output Gaussian processes via harmonizable spectral mixturesMatías Altamirano, Felipe A. Tobar. 3204-3218 [doi]
• Learning Quantile Functions for Temporal Point Processes with Recurrent Neural SplinesSouhaib Ben Taieb. 3219-3241 [doi]
• Differentially Private Regression with Unbounded CovariatesJason Milionis, Alkis Kalavasis, Dimitris A. Fotakis, Stratis Ioannidis. 3242-3273 [doi]
• Triple-Q: A Model-Free Algorithm for Constrained Reinforcement Learning with Sublinear Regret and Zero Constraint ViolationHonghao Wei, Xin Liu 0049, Lei Ying. 3274-3307 [doi]
• Measuring the robustness of Gaussian processes to kernel choiceWilliam T. Stephenson, Soumya Ghosh, Tin D. Nguyen, Mikhail Yurochkin, Sameer K. Deshpande, Tamara Broderick. 3308-3331 [doi]
• A general sample complexity analysis of vanilla policy gradientRui Yuan, Robert M. Gower, Alessandro Lazaric. 3332-3380 [doi]
• Pairwise Fairness for Ordinal RegressionMatthäus Kleindessner, Samira Samadi, Muhammad Bilal Zafar, Krishnaram Kenthapadi, Chris Russell 0001. 3381-3417 [doi]
• LIMESegment: Meaningful, Realistic Time Series ExplanationsTorty Sivill, Peter Flach. 3418-3433 [doi]
• A Random Matrix Perspective on Mixtures of Nonlinearities in High DimensionsBen Adlam, Jake A. Levinson, Jeffrey Pennington. 3434-3457 [doi]
• Spectral Pruning for Recurrent Neural NetworksTakashi Furuya, Kazuma Suetake, Koichi Taniguchi, Hiroyuki Kusumoto, Ryuji Saiin, Tomohiro Daimon. 3458-3482 [doi]
• Many processors, little time: MCMC for partitions via optimal transport couplingsTin D. Nguyen, Brian L. Trippe, Tamara Broderick. 3483-3514 [doi]
• Sinkformers: Transformers with Doubly Stochastic AttentionMichael E. Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré. 3515-3530 [doi]
• Finding Nearly Everything within Random Binary NetworksKartik Sreenivasan, Shashank Rajput, Jy-yong Sohn, Dimitris S. Papailiopoulos. 3531-3541 [doi]
• Last Layer Marginal Likelihood for Invariance LearningPola Schwöbel, Martin Jørgensen, Sebastian W. Ober, Mark van der Wilk. 3542-3555 [doi]
• Minimax Optimization: The Case of Convex-SubmodularArman Adibi, Aryan Mokhtari, Hamed Hassani. 3556-3580 [doi]
• Federated Learning with Buffered Asynchronous AggregationJohn Nguyen, Kshitiz Malik, Hongyuan Zhan, Ashkan Yousefpour, Mike Rabbat, Mani Malek 0001, Dzmitry Huba. 3581-3607 [doi]
• Bayesian Inference and Partial Identification in Multi-Treatment Causal Inference with Unobserved ConfoundingJiajing Zheng, Alexander D'Amour, Alexander Franks. 3608-3626 [doi]
• Deep Neyman-Scott ProcessesChengkuan Hong, Christian R. Shelton. 3627-3646 [doi]
• CATVI: Conditional and Adaptively Truncated Variational Inference for Hierarchical Bayesian Nonparametric ModelsJones Yirui Liu, Xinghao Qiao, Jessica Lam. 3647-3662 [doi]
• Certifiably Robust Variational AutoencodersBen Barrett, Alexander Camuto, Matthew Willetts, Tom Rainforth. 3663-3683 [doi]
• Practical Schemes for Finding Near-Stationary Points of Convex Finite-SumsKaiwen Zhou, Lai Tian, Anthony Man-Cho So, James Cheng. 3684-3708 [doi]
• On Margins and Derandomisation in PAC-BayesFelix Biggs, Benjamin Guedj. 3709-3731 [doi]
• A Spectral Perspective of DNN Robustness to Label NoiseOshrat Bar, Amnon Drory, Raja Giryes. 3732-3752 [doi]
• Momentum Accelerates the Convergence of Stochastic AUPRC MaximizationGuanghui Wang 0006, Ming Yang, Lijun Zhang, Tianbao Yang. 3753-3771 [doi]
• Computing D-Stationary Points of ρ-Margin Loss SVMLai Tian, Anthony Man-Cho So. 3772-3793 [doi]
• A Class of Geometric Structures in Transfer Learning: Minimax Bounds and OptimalityXuhui Zhang, José H. Blanchet, Soumyadip Ghosh, Mark S. Squillante. 3794-3820 [doi]
• An Information-Theoretic Justification for Model PruningBerivan Isik, Tsachy Weissman, Albert No. 3821-3846 [doi]
• Flexible Accuracy for Differential PrivacyAman Bansal, Rahul Chunduru, Deepesh Data, Manoj Prabhakaran. 3847-3882 [doi]
• Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function ApproximationYue Wu, Dongruo Zhou, Quanquan Gu. 3883-3913 [doi]
• On Facility Location Problem in the Local Differential Privacy ModelVincent Cohen-Addad, Yunus Esencayi, Chenglin Fan, Marco Gaboardi, Shi Li 0001, Di Wang 0015. 3914-3929 [doi]
• Towards Statistical and Computational Complexities of Polyak Step Size Gradient DescentTongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho. 3930-3961 [doi]
• MLDemon: Deployment Monitoring for Machine Learning SystemsTony Ginart, Martin Jinye Zhang, James Zou. 3962-3997 [doi]
• How to Learn when Data Gradually Reacts to Your ModelZachary Izzo, James Zou 0001, Lexing Ying. 3998-4035 [doi]
• Mitigating Bias in Calibration Error EstimationRebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer. 4036-4054 [doi]
• Privacy Amplification by Subsampling in Time DomainTatsuki Koga, Casey Meehan, Kamalika Chaudhuri. 4055-4069 [doi]
• How and When Random Feedback Works: A Case Study of Low-Rank Matrix FactorizationShivam Garg, Santosh S. Vempala. 4070-4108 [doi]
• Gap-Dependent Unsupervised Exploration for Reinforcement LearningJingfeng Wu, Vladimir Braverman, Lin Yang 0011. 4109-4131 [doi]
• On the Generalization of Representations in Reinforcement LearningCharline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare. 4132-4157 [doi]
• Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal EffectsYao Zhang, Jeroen Berrevoets, Mihaela van der Schaar. 4158-4177 [doi]
• Learning a Single Neuron for Non-monotonic Activation FunctionsLei Wu. 4178-4197 [doi]
• Can Pretext-Based Self-Supervised Learning Be Boosted by Downstream Data? A Theoretical AnalysisJiaye Teng, Weiran Huang 0001, Haowei He. 4198-4216 [doi]
• Model-free Policy Learning with Reward GradientsQingfeng Lan, Samuele Tosatto, Homayoon Farrahi, Rupam Mahmood. 4217-4234 [doi]
• Preference Exploration for Efficient Bayesian Optimization with Multiple OutcomesZhiyuan (Jerry) Lin, Raul Astudillo, Peter I. Frazier, Eytan Bakshy. 4235-4258 [doi]
• Near-optimal Policy Optimization Algorithms for Learning Adversarial Linear Mixture MDPsJiafan He, Dongruo Zhou, Quanquan Gu. 4259-4280 [doi]
• Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax OptimizationKiran Koshy Thekumparampil, Niao He, Sewoong Oh. 4281-4308 [doi]
• Denoising and change point localisation in piecewise-constant high-dimensional regression coefficientsFan Wang, Oscar Hernan Madrid Padilla, Yi Yu, Alessandro Rinaldo. 4309-4338 [doi]
• Optimal partition recovery in general graphsYi Yu, Oscar Madrid, Alessandro Rinaldo. 4339-4358 [doi]
• On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based OptimizationJungtaek Kim 0001, Seungjin Choi. 4359-4375 [doi]
• Offline Policy Selection under UncertaintyMengjiao Yang, Bo Dai, Ofir Nachum, George Tucker, Dale Schuurmans. 4376-4396 [doi]
• On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational ComplexityKhang Le, Huy Nguyen, Khai Nguyen, Tung Pham 0001, Nhat Ho. 4397-4413 [doi]
• Independent Natural Policy Gradient always converges in Markov Potential GamesRoy Fox, Stephen M. McAleer, Will Overman, Ioannis Panageas. 4414-4425 [doi]
• Semi-Implicit Hybrid Gradient Methods with Application to Adversarial RobustnessBeomsu Kim, Junghoon Seo. 4426-4445 [doi]
• Projection Predictive Inference for Generalized Linear and Additive Multilevel ModelsAlejandro Catalina, Paul-Christian Bürkner, Aki Vehtari. 4446-4461 [doi]
• Point Cloud Generation with Continuous ConditioningLarissa T. Triess, Andre Bühler, David Peter, Fabian B. Flohr, Marius Zöllner 0001. 4462-4481 [doi]
• An Optimal Algorithm for Strongly Convex Minimization under Affine ConstraintsAdil Salim, Laurent Condat, Dmitry Kovalev, Peter Richtárik. 4482-4498 [doi]
• CF-GNNExplainer: Counterfactual Explanations for Graph Neural NetworksAna Lucic, Maartje A. ter Hoeve, Gabriele Tolomei, Maarten de Rijke, Fabrizio Silvestri. 4499-4511 [doi]
• Safe Active Learning for Multi-Output Gaussian ProcessesCen-You Li, Barbara Rakitsch, Christoph Zimmer. 4512-4551 [doi]
• Variational Continual Proxy-Anchor for Deep Metric LearningMinyoung Kim, Ricardo Guerrero, Hai Xuan Pham, Vladimir Pavlovic. 4552-4573 [doi]
• Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical AnalysisMartin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju. 4574-4594 [doi]
• Variational Autoencoders: A Harmonic PerspectiveAlexander Camuto, Matthew Willetts. 4595-4611 [doi]
• On the Consistency of Max-Margin LossesAlex Nowak, Alessandro Rudi, Francis Bach. 4612-4633 [doi]
• A prior-based approximate latent Riemannian metricGeorgios Arvanitidis, Bogdan M. Georgiev, Bernhard Schölkopf. 4634-4658 [doi]
• On Convergence of Lookahead in Smooth GamesJunsoo Ha, Gunhee Kim. 4659-4684 [doi]
• Learning Proposals for Practical Energy-Based RegressionFredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön. 4685-4704 [doi]
• Predicting the impact of treatments over time with uncertainty aware neural differential equationsEdward De Brouwer, Javier Gonzalez, Stephanie L. Hyland. 4705-4722 [doi]
• Improved Algorithms for Misspecified Linear Markov Decision ProcessesDaniel Vial, Advait Parulekar, Sanjay Shakkottai, R. Srikant 0001. 4723-4746 [doi]
• Synthsonic: Fast, Probabilistic modeling and Synthesis of Tabular DataMax Baak, Simon Brugman, Ilan Fridman Rojas, Lorraine Dalmeida, Ralph E. Q. Urlus, Jean-Baptiste Oger. 4747-4763 [doi]
• Lagrangian manifold Monte Carlo on Monge patchesMarcelo Hartmann, Mark Girolami, Arto Klami. 4764-4781 [doi]
• Optimal Accounting of Differential Privacy via Characteristic FunctionYuqing Zhu 0005, Jinshuo Dong, Yu-Xiang Wang. 4782-4817 [doi]
• Adaptive Gaussian Processes on Graphs via Spectral Graph WaveletsFelix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong 0001. 4818-4834 [doi]
• Bayesian Link Prediction with Deep Graph Convolutional Gaussian ProcessesFelix L. Opolka, Pietro Liò. 4835-4852 [doi]
• On the Interplay between Information Loss and Operation Loss in Representations for ClassificationJorge Silva, Felipe A. Tobar. 4853-4871 [doi]
• Pulling back information geometryGeorgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitrios Kalatzis, Søren Hauberg. 4872-4894 [doi]
• Optimizing Early Warning Classifiers to Control False Alarms via a Minimum Precision ConstraintPreetish Rath, Michael Hughes. 4895-4914 [doi]
• Resampling Base Distributions of Normalizing FlowsVincent Stimper, Bernhard Schölkopf, José Miguel Hernández-Lobato. 4915-4936 [doi]
• Federated Myopic Community Detection with One-shot CommunicationChuyang Ke, Jean Honorio. 4937-4954 [doi]
• Variational Gaussian Processes: A Functional Analysis ViewGeorge Wynne, Veit Wild. 4955-4971 [doi]
• Adversarially Robust Kernel SmoothingJia-Jie Zhu, Christina Kouridi, Yassine Nemmour, Bernhard Schölkopf. 4972-4994 [doi]
• Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-WolfeThibault Séjourné, François-Xavier Vialard, Gabriel Peyré. 4995-5021 [doi]
• Off-Policy Risk Assessment for Markov Decision ProcessesAudrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli. 5022-5050 [doi]
• Predictive variational Bayesian inference as risk-seeking optimizationFutoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama. 5051-5083 [doi]
• Kantorovich Mechanism for Pufferfish PrivacyNi Ding. 5084-5103 [doi]
• Margin-distancing for safe model explanationTom Yan, Chicheng Zhang. 5104-5134 [doi]
• Optimal transport with f-divergence regularization and generalized Sinkhorn algorithmDávid Terjék, Diego González-Sánchez. 5135-5165 [doi]
• Modelling Non-Smooth Signals with Complex Spectral StructureWessel P. Bruinsma, Martin Tegner, Richard E. Turner. 5166-5195 [doi]
• Convergent Working Set Algorithm for Lasso with Non-Convex Sparse RegularizersAlain Rakotomamonjy, Rémi Flamary, Joseph Salmon, Gilles Gasso. 5196-5211 [doi]
• Particle-based Adversarial Local Distribution RegularizationThanh Nguyen-Duc, Trung Le, He Zhao 0001, Jianfei Cai 0001, Dinh Q. Phung. 5212-5224 [doi]
• Crowdsourcing Regression: A Spectral ApproachYaniv Tenzer, Omer Dror, Boaz Nadler, Erhan Bilal, Yuval Kluger. 5225-5242 [doi]
• How to scale hyperparameters for quickshift image segmentationDamien Garreau. 5243-5275 [doi]
• Wide Mean-Field Bayesian Neural Networks Ignore the DataBeau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez. 5276-5333 [doi]
• Privacy Amplification by DecentralizationEdwige Cyffers, Aurélien Bellet. 5334-5353 [doi]
• Reinforcement Learning with Fast Stabilization in Linear Dynamical SystemsSahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Animashree Anandkumar. 5354-5390 [doi]
• New Coresets for Projective Clustering and ApplicationsMurad Tukan, Xuan Wu 0002, Samson Zhou, Vladimir Braverman, Dan Feldman. 5391-5415 [doi]
• Weak Separation in Mixture Models and Implications for Principal StratificationNhat Ho, Avi Feller, Evan Greif, Luke Miratrix, Natesh Pillai. 5416-5458 [doi]
• Using time-series privileged information for provably efficient learning of prediction modelsRickard K. A. Karlsson, Martin Willbo, Zeshan M. Hussain, Rahul G. Krishnan, David A. Sontag, Fredrik Johansson 0002. 5459-5484 [doi]
• Faster Single-loop Algorithms for Minimax Optimization without Strong ConcavityJunchi Yang, Antonio Orvieto, Aurélien Lucchi, Niao He. 5485-5517 [doi]
• TD-GEN: Graph Generation Using Tree DecompositionHamed Shirzad, Hossein Hajimirsadeghi, Amir H. Abdi, Greg Mori. 5518-5537 [doi]
• Finding Valid Adjustments under Non-ignorability with Minimal DAG KnowledgeAbhin Shah, Karthikeyan Shanmugam, Kartik Ahuja. 5538-5562 [doi]
• SHAFF: Fast and consistent SHApley eFfect estimates via random ForestsClément Bénard, Gérard Biau, Sébastien Da Veiga, Erwan Scornet. 5563-5582 [doi]
• Almost Optimal Universal Lower Bound for Learning Causal DAGs with Atomic InterventionsVibhor Porwal, Piyush Srivastava, Gaurav Sinha. 5583-5603 [doi]
• Estimators of Entropy and Information via Inference in Probabilistic ModelsFeras Saad, Marco Cusumano-Towner, Vikash Mansinghka 0001. 5604-5621 [doi]
• Adaptive Private-K-Selection with Adaptive K and Application to Multi-label PATEYuqing Zhu 0005, Yu-Xiang Wang. 5622-5635 [doi]
• Fast and accurate optimization on the orthogonal manifold without retractionPierre Ablin, Gabriel Peyré. 5636-5657 [doi]
• Beyond the Policy Gradient Theorem for Efficient Policy Updates in Actor-Critic AlgorithmsRomain Laroche, Remi Tachet des Combes. 5658-5688 [doi]
• Efficient Kernelized UCB for Contextual BanditsHoussam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard. 5689-5720 [doi]
• Acceleration in Distributed Optimization under SimilarityYe Tian 0021, Gesualdo Scutari, Tianyu Cao, Alexander V. Gasnikov. 5721-5756 [doi]
• Corruption-robust Offline Reinforcement LearningXuezhou Zhang, Yiding Chen, Xiaojin Zhu 0001, Wen Sun. 5757-5773 [doi]
• A Cramér Distance perspective on Quantile Regression based Distributional Reinforcement LearningAlix Lheritier, Nicolas Bondoux. 5774-5789 [doi]
• Orbital MCMCKirill Neklyudov, Max Welling. 5790-5814 [doi]
• PAC Mode Estimation using PPR Martingale Confidence SequencesShubham Anand Jain, Rohan Shah, Sanit Gupta, Denil Mehta, Inderjeet J. Nair, Jian Vora, Sushil Khyalia, Sourav Das, Vinay J. Ribeiro, Shivaram Kalyanakrishnan. 5815-5852 [doi]
• Harmless interpolation in regression and classification with structured featuresAndrew D. McRae, Santhosh Karnik, Mark A. Davenport, Vidya K. Muthukumar. 5853-5875 [doi]
• Masked Training of Neural Networks with Partial GradientsAmirkeivan Mohtashami, Martin Jaggi, Sebastian U. Stich. 5876-5890 [doi]
• Learning in Stochastic Monotone Games with Decision-Dependent DataAdhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian J. Ratliff. 5891-5912 [doi]
• On Combining Bags to Better Learn from Label ProportionsRishi Saket, Aravindan Raghuveer, Balaraman Ravindran. 5913-5927 [doi]
• Meta Learning MDPs with linear transition modelsRobert Müller, Aldo Pacchiano. 5928-5948 [doi]
• Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow ProposalsJames A. Brofos, Marylou Gabrié, Marcus A. Brubaker, Roy R. Lederman. 5949-5986 [doi]
• Permutation Equivariant Layers for Higher Order InteractionsHorace Pan, Risi Kondor. 5987-6001 [doi]
• Efficient Online Bayesian Inference for Neural BanditsGerardo Duran-Martin, Aleyna Kara, Kevin Murphy. 6002-6021 [doi]
• Parameter-Free Online Linear Optimization with Side Information via Universal Coin BettingJongha J. Ryu, Alankrita Bhatt, Young-Han Kim 0001. 6022-6044 [doi]
• Performative Prediction in a Stateful WorldGavin Brown, Shlomi Hod, Iden Kalemaj. 6045-6061 [doi]
• Learning Revenue-Maximizing Auctions With Differentiable MatchingMichael J. Curry, Uro Lyi, Tom Goldstein, John P. Dickerson. 6062-6073 [doi]
• Orthogonal Multi-Manifold Enriching of Directed NetworksRamit Sawhney, Shivam Agarwal, Atula Tejaswi Neerkaje, Kapil Jayesh Pathak. 6074-6086 [doi]
• Estimating Functionals of the Out-of-Sample Error Distribution in High-Dimensional Ridge RegressionPratik Patil, Alessandro Rinaldo, Ryan J. Tibshirani. 6087-6120 [doi]
• The Tree Loss: Improving Generalization with Many ClassesYujie Wang, Mike Izbicki. 6121-6133 [doi]
• Double Control Variates for Gradient Estimation in Discrete Latent Variable ModelsMichalis K. Titsias, Jiaxin Shi. 6134-6151 [doi]
• Transfer Learning with Gaussian Processes for Bayesian OptimizationPetru Tighineanu, Kathrin Skubch, Paul Baireuther, Attila Reiss, Felix Berkenkamp, Julia Vinogradska. 6152-6181 [doi]
• Conditional Linear Regression for Heterogeneous CovariancesLeda Liang, Brendan Juba. 6182-6199 [doi]
• Learning Competitive Equilibria in Exchange Economies with Bandit FeedbackWenshuo Guo, Kirthevasan Kandasamy, Joseph Gonzalez 0001, Michael I. Jordan, Ion Stoica. 6200-6224 [doi]
• Node Feature Kernels Increase Graph Convolutional Network RobustnessMohamed-El-Amine Seddik, Changmin Wu, Johannes F. Lutzeyer, Michalis Vazirgiannis. 6225-6241 [doi]
• Top K Ranking for Multi-Armed Bandit with Noisy EvaluationsEvrard Garcelon, Vashist Avadhanula, Alessandro Lazaric, Matteo Pirotta. 6242-6269 [doi]
• Differential privacy for symmetric log-concave mechanismsStaal A. Vinterbo. 6270-6291 [doi]
• Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex OptimizationYujia Wang, Lu Lin, Jinghui Chen. 6292-6320 [doi]
• Fair Disaster Containment via Graph-Cut ProblemsMichael Dinitz, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti. 6321-6333 [doi]
• Provable Lifelong Learning of RepresentationsXinyuan Cao, Weiyang Liu, Santosh S. Vempala. 6334-6356 [doi]
• Learning from an Exploring Demonstrator: Optimal Reward Estimation for BanditsWenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya K. Muthukumar, Ashwin Pananjady. 6357-6386 [doi]
• A New Notion of Individually Fair Clustering: α-Equitable k-CenterDarshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas. 6387-6408 [doi]
• Iterative Alignment FlowsZeyu Zhou, Ziyu Gong, Pradeep Ravikumar, David I. Inouye. 6409-6444 [doi]
• Fast Fourier Transform Reductions for Bayesian Network InferenceVincent Hsiao, Dana S. Nau, Rina Dechter. 6445-6458 [doi]
• QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated LearningMaxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines. 6459-6500 [doi]
• Lifted Division for Lifted Hugin Belief PropagationMoritz P. Hoffmann, Tanya Braun, Ralf Möller 0001. 6501-6510 [doi]
• Proximal Optimal Transport Modeling of Population DynamicsCharlotte Bunne, Laetitia Papaxanthos, Andreas Krause 0001, Marco Cuturi. 6511-6528 [doi]
• Asynchronous Upper Confidence Bound Algorithms for Federated Linear BanditsChuanhao Li, Hongning Wang. 6529-6553 [doi]
• Efficient Hyperparameter Tuning for Large Scale Kernel Ridge RegressionGiacomo Meanti, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco. 6554-6572 [doi]
• Are All Linear Regions Created Equal?Matteo Gamba, Adrian Chmielewski-Anders, Josephine Sullivan, Hossein Azizpour, Mårten Björkman. 6573-6590 [doi]
• Entrywise Recovery Guarantees for Sparse PCA via Sparsistent AlgorithmsJoshua Agterberg, Jeremias Sulam. 6591-6629 [doi]
• An Alternate Policy Gradient Estimator for Softmax PoliciesShivam Garg 0006, Samuele Tosatto, Yangchen Pan, Martha White, Rupam Mahmood. 6630-6689 [doi]
• Co-Regularized Adversarial Learning for Multi-Domain Text ClassificationYuan Wu 0002, Diana Inkpen, Ahmed El-Roby. 6690-6701 [doi]
• Zeroth-Order Methods for Convex-Concave Min-max Problems: Applications to Decision-Dependent Risk MinimizationChinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, Shankar Sastry 0001, Lillian J. Ratliff. 6702-6734 [doi]
• Near Instance Optimal Model Selection for Pure Exploration Linear BanditsYinglun Zhu, Julian Katz-Samuels, Robert D. Nowak. 6735-6769 [doi]
• Identification in Tree-shaped Linear Structural Causal ModelsBenito van der Zander, Marcel Wienöbst, Markus Bläser, Maciej Liskiewicz. 6770-6792 [doi]
• Pareto Optimal Model Selection in Linear BanditsYinglun Zhu, Robert D. Nowak. 6793-6813 [doi]
• PAC Top-k Identification under SST in Limited RoundsArpit Agarwal, Sanjeev Khanna, Prathamesh Patil. 6814-6839 [doi]
• Local SGD Optimizes Overparameterized Neural Networks in Polynomial TimeYuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi. 6840-6861 [doi]
• Dual-Level Adaptive Information Filtering for Interactive Image SegmentationErvine Zheng, Qi Yu 0001, Rui Li 0002, Pengcheng Shi, Anne R. Haake. 6862-6879 [doi]
• On the Value of Prior in Online Learning to RankBranislav Kveton, Ofer Meshi, Masrour Zoghi, Zhen Qin. 6880-6892 [doi]
• Doubly Mixed-Effects Gaussian Process RegressionJun Ho Yoon, Daniel P. Jeong, Seyoung Kim. 6893-6908 [doi]
• Weighted Gaussian Process Bandits for Non-stationary EnvironmentsYuntian Deng, Xingyu Zhou 0001, Baekjin Kim, Ambuj Tewari, Abhishek Gupta 0002, Ness B. Shroff. 6909-6932 [doi]
• Conditionally Tractable Density Estimation using Neural NetworksHailiang Dong, Chiradeep Roy, Tahrima Rahman, Vibhav Gogate, Nicholas Ruozzi. 6933-6946 [doi]
• Common Information based Approximate State Representations in Multi-Agent Reinforcement LearningHsu Kao, Vijay G. Subramanian. 6947-6967 [doi]
• Sensing Cox Processes via Posterior Sampling and Positive BasesMojmir Mutny, Andreas Krause 0001. 6968-6989 [doi]
• A Predictive Approach to Bayesian Nonparametric Survival AnalysisEdwin Fong, Brieuc Lehmann. 6990-7013 [doi]
• On the equivalence of Oja's algorithm and GROUSELaura Balzano. 7014-7030 [doi]
• Diversified Sampling for Batched Bayesian Optimization with Determinantal Point ProcessesElvis Nava, Mojmir Mutny, Andreas Krause 0001. 7031-7054 [doi]
• Label differential privacy via clusteringHossein Esfandiari, Vahab S. Mirrokni, Umar Syed, Sergei Vassilvitskii. 7055-7075 [doi]
• Neural score matching for high-dimensional causal inferenceOscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris C. Holmes. 7076-7110 [doi]
• Robust Stochastic Linear Contextual Bandits Under Adversarial AttacksQin Ding 0002, Cho-Jui Hsieh, James Sharpnack. 7111-7123 [doi]
• Multi-class classification in nonparametric active learningBoris Ndjia Njike, Xavier Siebert. 7124-7162 [doi]
• On the Assumptions of Synthetic Control MethodsClaudia Shi, Dhanya Sridhar, Vishal Misra, David M. Blei. 7163-7175 [doi]
• Faster Rates, Adaptive Algorithms, and Finite-Time Bounds for Linear Composition Optimization and Gradient TD LearningAnant Raj, Pooria Joulani, András György 0001, Csaba Szepesvári. 7176-7186 [doi]
• Investigating the Role of Negatives in Contrastive Representation LearningJordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra. 7187-7209 [doi]
• Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal InferenceAmirEmad Ghassami, Andrew Ying, Ilya Shpitser, Eric Tchetgen Tchetgen. 7210-7239 [doi]
• Derivative-Based Neural Modelling of Cumulative Distribution Functions for Survival AnalysisDominic Danks, Christopher Yau. 7240-7256 [doi]
• Cycle Consistent Probability Divergences Across Different SpacesZhengxin Zhang, Youssef Mroueh, Ziv Goldfeld, Bharath K. Sriperumbudur. 7257-7285 [doi]
• Warping Layer: Representation Learning for Label Structures in Weakly Supervised LearningYingyi Ma, Xinhua Zhang. 7286-7299 [doi]
• A Bandit Model for Human-Machine Decision Making with Private Information and OpacitySebastian Bordt, Ulrike von Luxburg. 7300-7319 [doi]
• Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive DiscretizationMarco Rando, Luigi Carratino, Silvia Villa, Lorenzo Rosasco. 7320-7348 [doi]
• Adaptive Multi-Goal ExplorationJean Tarbouriech, Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Michal Valko, Alessandro Lazaric. 7349-7383 [doi]
• Chernoff Sampling for Active Testing and Extension to Active RegressionSubhojyoti Mukherjee, Ardhendu S. Tripathy, Robert D. Nowak. 7384-7432 [doi]
• An Information-theoretical Approach to Semi-supervised Learning under Covariate-shiftGholamali Aminian, Mahed Abroshan, Mohammad Mahdi Khalili, Laura Toni, Miguel R. D. Rodrigues. 7433-7449 [doi]
• Optimal Design of Stochastic DNA Synthesis Protocols based on Generative Sequence ModelsEli N. Weinstein, Alan N. Amin, Will S. Grathwohl, Daniel Kassler, Jean Disset, Debora Marks. 7450-7482 [doi]
• Approximate Top-m Arm Identification with Heterogeneous Reward VariancesRuida Zhou, Chao Tian 0002. 7483-7504 [doi]
• On perfectness in Gaussian graphical modelsArash A. Amini, Bryon Aragam, Qing Zhou. 7505-7517 [doi]
• GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RLSumedh A. Sontakke, Stephen Iota, Zizhao Hu, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf. 7518-7530 [doi]
• Efficient interventional distribution learning in the PAC frameworkArnab Bhattacharyya 0001, Sutanu Gayen, Saravanan Kandasamy 0002, Vedant Raval, N. Variyam Vinodchandran. 7531-7549 [doi]
• Dropout as a Regularizer of Interaction EffectsBenjamin J. Lengerich, Eric P. Xing, Rich Caruana. 7550-7564 [doi]
• Thompson Sampling with a Mixture PriorJoey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier. 7565-7586 [doi]
• SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with SparsificationAshwinee Panda, Saeed Mahloujifar, Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal. 7587-7624 [doi]
• Nearly Optimal Algorithms for Level Set EstimationBlake Mason, Lalit Jain, Subhojyoti Mukherjee, Romain Camilleri, Kevin G. Jamieson, Robert D. Nowak. 7625-7658 [doi]
• Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax OptimizationGuodong Zhang, Yuanhao Wang 0001, Laurent Lessard, Roger B. Grosse. 7659-7679 [doi]
• Optimal Compression of Locally Differentially Private MechanismsAbhin Shah, Wei-Ning Chen, Johannes Ballé, Peter Kairouz, Lucas Theis. 7680-7723 [doi]
• Hierarchical Bayesian BanditsJoey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh. 7724-7741 [doi]
• Complex Momentum for Optimization in GamesJonathan P. Lorraine, David Acuna, Paul Vicol, David Duvenaud. 7742-7765 [doi]
• Asymptotically Optimal Locally Private Heavy Hitters via Parameterized SketchesHao Wu, Anthony Wirth. 7766-7798 [doi]
• Tuning-Free Generalized Hamiltonian Monte CarloMatthew D. Hoffman, Pavel Sountsov. 7799-7813 [doi]
• Federated Functional Gradient BoostingZebang Shen, Hamed Hassani, Satyen Kale, Amin Karbasi. 7814-7840 [doi]
• Generalised GPLVM with Stochastic Variational InferenceVidhi Lalchand, Aditya Ravuri, Neil D. Lawrence. 7841-7864 [doi]
• Stochastic Extragradient: General Analysis and Improved RatesEduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou. 7865-7901 [doi]
• Deep Non-crossing Quantiles through the Partial DerivativeBrando Axel, Joan Gimeno, José A. Rodríguez-Serrano, Jordi Vitria. 7902-7914 [doi]
• Optimal channel selection with discrete QCQPYeonwoo Jeong, Deokjae Lee, Gaon An, Changyong Son, Hyun Oh Song. 7915-7941 [doi]
• Vanishing Curvature in Randomly Initialized Deep ReLU NetworksAntonio Orvieto, Jonas Kohler, Dario Pavllo, Thomas Hofmann, Aurélien Lucchi. 7942-7975 [doi]
• Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian ProcessesHugh Dance, Brooks Paige. 7976-8002 [doi]
• Self-training Converts Weak Learners to Strong Learners in Mixture ModelsSpencer Frei, Difan Zou, Zixiang Chen, Quanquan Gu. 8003-8021 [doi]
• Two-Sample Test with Kernel Projected Wasserstein DistanceJie Wang, Rui Gao, Yao Xie. 8022-8055 [doi]
• Mode estimation on matrix manifolds: Convergence and robustnessHiroaki Sasaki, Jun-ichiro Hirayama, Takafumi Kanamori. 8056-8079 [doi]
• A Dimensionality Reduction Method for Finding Least Favorable Priors with a Focus on Bregman DivergenceAlex R. Dytso, Mario Goldenbaum, H. Vincent Poor, Shlomo Shamai. 8080-8094 [doi]
• Towards Federated Bayesian Network Structure Learning with Continuous OptimizationIgnavier Ng, Kun Zhang 0001. 8095-8111 [doi]
• Nuances in Margin Conditions Determine Gains in Active LearningSamory Kpotufe, Gan Yuan, Yunfan Zhao. 8112-8126 [doi]
• Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series ForecastingYoungsuk Park, Danielle C. Maddix, François-Xavier Aubet, Kelvin Kan, Jan Gasthaus, Yuyang Wang. 8127-8150 [doi]
• Convergence of Langevin Monte Carlo in Chi-Squared and Rényi DivergenceMurat A. Erdogdu, Rasa Hosseinzadeh, Shunshi Zhang. 8151-8175 [doi]
• On the Convergence of Continuous Constrained Optimization for Structure LearningIgnavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang 0001. 8176-8198 [doi]
• Hardness of Learning a Single Neuron with Adversarial Label NoiseIlias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren. 8199-8213 [doi]
• Firebolt: Weak Supervision Under Weaker AssumptionsZhaobin Kuang, Chidubem G. Arachie, Bangyong Liang, Pradyumna Narayana, Giulia DeSalvo, Michael S. Quinn, Bert Huang, Geoffrey Downs, Yang Yang. 8214-8259 [doi]
• Relational Neural Markov Random FieldsYuqiao Chen, Sriraam Natarajan, Nicholas Ruozzi. 8260-8269 [doi]
• PACm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian RegimeWarren R. Morningstar, Alex Alemi, Joshua V. Dillon. 8270-8298 [doi]
• Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization LandscapeDevansh Bisla, Jing Wang, Anna Choromanska. 8299-8339 [doi]
• Online Control of the False Discovery Rate under "Decision Deadlines"Aaron J. Fisher. 8340-8359 [doi]
• Tile Networks: Learning Optimal Geometric Layout for Whole-page RecommendationShuai Xiao, Zaifan Jiang, Shuang Yang. 8360-8369 [doi]
• A Bayesian Approach for Stochastic Continuum-armed Bandit with Long-term ConstraintsZai Shi, Atilla Eryilmaz. 8370-8391 [doi]
• Amortized Rejection Sampling in Universal Probabilistic ProgrammingSaeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Gunes Baydin, Bradley J. Gram-Hansen, Christian A. Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood. 8392-8412 [doi]
• The Curse of Passive Data Collection in Batch Reinforcement LearningChenjun Xiao, Ilbin Lee, Bo Dai, Dale Schuurmans, Csaba Szepesvári. 8413-8438 [doi]
• Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex MinimizationGideon Dresdner, Maria-Luiza Vladarean, Gunnar Rätsch, Francesco Locatello, Volkan Cevher, Alp Yurtsever. 8439-8457 [doi]
• Adversarial Tracking Control via Strongly Adaptive Online Learning with MemoryZhiyu Zhang 0003, Ashok Cutkosky, Ioannis Ch. Paschalidis. 8458-8492 [doi]
• Look-Ahead Acquisition Functions for Bernoulli Level Set EstimationBenjamin Letham, Phillip Guan, Chase Tymms, Eytan Bakshy, Michael Shvartsman. 8493-8513 [doi]
• Debiasing Samples from Online Learning Using BootstrapNingyuan Chen, Xuefeng Gao, Yi Xiong. 8514-8533 [doi]
• Convergence of online k-meansGeelon So, Gaurav Mahajan, Sanjoy Dasgupta. 8534-8569 [doi]
• Reconstructing Test Labels from Noisy Loss FunctionsAbhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier. 8570-8591 [doi]
• Contrasting the landscape of contrastive and non-contrastive learningAshwini Pokle, Jinjin Tian, Yuchen Li, Andrej Risteski. 8592-8618 [doi]
• A general class of surrogate functions for stable and efficient reinforcement learningSharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux. 8619-8649 [doi]
• Fundamental limits for rank-one matrix estimation with groupwise heteroskedasticityJoshua K. Behne, Galen Reeves. 8650-8672 [doi]
• Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs AlgorithmYuheng Bu, Gholamali Aminian, Laura Toni, Gregory W. Wornell, Miguel Rodrigues. 8673-8699 [doi]
• Decoupling Local and Global Representations of Time SeriesSana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister. 8700-8714 [doi]
• Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit OptimizationHung Tran-The, Sunil Gupta 0001, Santu Rana, Svetha Venkatesh. 8715-8737 [doi]
• Optimal estimation of Gaussian DAG modelsMing Gao, Wai Ming Tai, Bryon Aragam. 8738-8757 [doi]
• Improved Approximation Algorithms for Individually Fair ClusteringAli Vakilian, Mustafa Yalçiner. 8758-8779 [doi]
• Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine LearningYongchan Kwon, James Zou 0001. 8780-8802 [doi]
• Variance Minimization in the Wasserstein Space for Invariant Causal PredictionGuillaume G. Martinet, Alexander Strzalkowski, Barbara E. Engelhardt. 8803-8851 [doi]
• Online Continual Adaptation with Active Self-TrainingShiji Zhou, Han Zhao 0002, Shanghang Zhang, Lianzhe Wang, Heng Chang, Zhi Wang, Wenwu Zhu 0001. 8852-8883 [doi]
• Structured variational inference in Bayesian state-space modelsHonggang Wang, Anirban Bhattacharya, Debdeep Pati, Yun Yang. 8884-8905 [doi]
• Structured Multi-task Learning for Molecular Property PredictionShengchao Liu, Meng Qu, Zuobai Zhang, Huiyu Cai, Jian Tang 0005. 8906-8920 [doi]
• Nonparametric Relational Models with SuperrectangulationMasahiro Nakano, Ryo Nishikimi, Yasuhiro Fujiwara, Akisato Kimura, Takeshi Yamada, Naonori Ueda. 8921-8937 [doi]
• Regret, stability & fairness in matching markets with bandit learnersSarah Huiyi Cen, Devavrat Shah. 8938-8968 [doi]
• Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation MethodsChirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju. 8969-8996 [doi]
• Distributionally Robust Structure Learning for Discrete Pairwise Markov NetworksYeshu Li, Zhan Shi, Xinhua Zhang, Brian D. Ziebart. 8997-9016 [doi]
• ExactBoost: Directly Boosting the Margin in Combinatorial and Non-decomposable MetricsDaniel Csillag, Carolina Piazza, Thiago Ramos, João Vitor Romano, Roberto I. Oliveira, Paulo Orenstein. 9017-9049 [doi]
• Sharp Bounds for Federated Averaging (Local SGD) and Continuous PerspectiveMargalit R. Glasgow, Honglin Yuan, Tengyu Ma 0001. 9050-9090 [doi]
• Near-Optimal Task Selection for Meta-Learning with Mutual Information and Online Variational Bayesian UnlearningYizhou Chen, Shizhuo Zhang, Bryan Kian Hsiang Low. 9091-9113 [doi]
• Best Arm Identification with Safety ConstraintsZhenlin Wang, Andrew J. Wagenmaker, Kevin G. Jamieson. 9114-9146 [doi]
• On the complexity of the optimal transport problem with graph-structured costJiaoJiao Fan, Isabel Haasler, Johan Karlsson, Yongxin Chen. 9147-9165 [doi]
• Second-Order Sensitivity Analysis for Bilevel OptimizationRobert Dyro, Edward Schmerling, Nikos Aréchiga, Marco Pavone. 9166-9181 [doi]
• On Learning Mixture Models with Sparse ParametersSoumyabrata Pal, Arya Mazumdar. 9182-9213 [doi]
• Sketch-and-lift: scalable subsampled semidefinite program for K-means clusteringYubo Zhuang, Xiaohui Chen, Yun Yang. 9214-9246 [doi]
• Asynchronous Distributed Optimization with Stochastic DelaysMargalit R. Glasgow, Mary Wootters. 9247-9279 [doi]
• Calibration Error for Heterogeneous Treatment EffectsYizhe Xu, Steve Yadlowsky. 9280-9303 [doi]
• Fast Sparse Classification for Generalized Linear and Additive ModelsJiachang Liu 0001, Chudi Zhong, Margo I. Seltzer, Cynthia Rudin. 9304-9333 [doi]
• A Unified View of SDP-based Neural Network Verification through Completely Positive ProgrammingRobin A. Brown, Edward Schmerling, Navid Azizan, Marco Pavone. 9334-9355 [doi]
• Recoverability Landscape of Tree Structured Markov Random Fields under Symmetric NoiseAshish Katiyar, Soumya Basu 0001, Vatsal Shah, Constantine Caramanis. 9356-9399 [doi]
• Learning Sparse Fixed-Structure Gaussian Bayesian NetworksArnab Bhattacharyya 0001, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, Yuhao Wang. 9400-9429 [doi]
• Learning and Generalization in Overparameterized Normalizing FlowsKulin Shah, Amit Deshpande 0001, Navin Goyal. 9430-9504 [doi]
• Expressivity of Neural Networks via Chaotic Itineraries beyond Sharkovsky's TheoremClayton Hendrick Sanford, Vaggos Chatziafratis. 9505-9549 [doi]
• Learning Interpretable, Tree-Based Projection Mappings for Nonlinear EmbeddingsArman S. Zharmagambetov, Miguel Á. Carreira-Perpiñán. 9550-9570 [doi]
• Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time DataMatthew Engelhard, Ricardo Henao. 9571-9581 [doi]
• Sample Complexity of Robust Reinforcement Learning with a Generative ModelKishan Panaganti, Dileep M. Kalathil. 9582-9602 [doi]
• On Coresets for Fair Regression and Individually Fair ClusteringRachit Chhaya, Anirban Dasgupta 0001, Jayesh Choudhari, Supratim Shit. 9603-9625 [doi]
• LocoProp: Enhancing BackProp via Local Loss OptimizationEhsan Amid, Rohan Anil, Manfred K. Warmuth. 9626-9642 [doi]
• Towards Agnostic Feature-based Dynamic Pricing: Linear Policies vs Linear Valuation with Unknown NoiseJianyu Xu, Yu-Xiang Wang. 9643-9662 [doi]
• A cautionary tale on fitting decision trees to data from additive models: generalization lower boundsYan Shuo Tan, Abhineet Agarwal, Bin Yu 0001. 9663-9685 [doi]
• Exact Community Recovery over Signed GraphsXiaolu Wang, Peng Wang 0098, Anthony Man-Cho So. 9686-9710 [doi]
• Laplacian Constrained Precision Matrix Estimation: Existence and High Dimensional ConsistencyEduardo Pavez. 9711-9722 [doi]
• Primal-Dual Stochastic Mirror Descent for MDPsDaniil Tiapkin, Alexander V. Gasnikov. 9723-9740 [doi]
• Convex Analysis of the Mean Field Langevin DynamicsAtsushi Nitanda, Denny Wu, Taiji Suzuki. 9741-9757 [doi]
• Information-Theoretic Analysis of Epistemic Uncertainty in Bayesian Meta-learningSharu Theresa Jose, Sangwoo Park, Osvaldo Simeone. 9758-9775 [doi]
• Marginalising over Stationary Kernels with Bayesian QuadratureSaad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts. 9776-9792 [doi]
• On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration AveragingChris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma 0001, Nicolas Le Roux, Michael I. Jordan. 9793-9826 [doi]
• An Unsupervised Hunt for Gravitational LensesStephen Sheng, Keerthi Vasan G. C, Chi Po P. Choi, James Sharpnack, Tucker Jones. 9827-9843 [doi]
• Sobolev Transport: A Scalable Metric for Probability Measures with Graph MetricsTam Le, Truyen Nguyen, Dinh Phung, Viet Anh Nguyen. 9844-9868 [doi]
• Mean Nyström Embeddings for Adaptive Compressive LearningAntoine Chatalic, Luigi Carratino, Ernesto De Vito, Lorenzo Rosasco. 9869-9889 [doi]
• GraphAdaMix: Enhancing Node Representations with Graph Adaptive MixturesDa Sun Handason Tam, Siyue Xie, Wing Cheong Lau. 9890-9907 [doi]
• Provable Adversarial Robustness for Fractional Lp Threat ModelsAlexander Levine 0001, Soheil Feizi. 9908-9942 [doi]
• On Some Fast And Robust Classifiers For High Dimension, Low Sample Size DataSarbojit Roy, Jyotishka Ray Choudhury, Subhajit Dutta. 9943-9968 [doi]
• Learning Pareto-Efficient Decisions with ConfidenceSofia Ek, Dave Zachariah, Peter Stoica. 9969-9981 [doi]
• Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputsHarish Doddi, Deepjyoti Deka, Saurav Talukdar, Murti V. Salapaka. 9982-9997 [doi]
• Compressed Rule Ensemble LearningMalte Nalenz, Thomas Augustin. 9998-10014 [doi]
• Pick-and-Mix Information Operators for Probabilistic ODE SolversNathanael Bosch, Filip Tronarp, Philipp Hennig. 10015-10027 [doi]
• Finite Sample Analysis of Mean-Volatility Actor-Critic for Risk-Averse Reinforcement LearningKhaled Eldowa, Lorenzo Bisi, Marcello Restelli. 10028-10066 [doi]
• The Importance of Future Information in Credit Card Fraud DetectionVan Bach Nguyen, Kanishka Ghosh Dastidar, Michael Granitzer, Wissam Siblini. 10067-10077 [doi]
• A Non-asymptotic Approach to Best-Arm Identification for Gaussian BanditsAntoine Barrier, Aurélien Garivier, Tomás Kocák. 10078-10109 [doi]
• Differentially Private Federated Learning on Heterogeneous DataMaxence Noble, Aurélien Bellet, Aymeric Dieuleveut. 10110-10145 [doi]
• Efficient computation of the the volume of a polytope in high-dimensions using Piecewise Deterministic Markov ProcessesAugustin Chevallier, Frédéric Cazals, Paul Fearnhead. 10146-10160 [doi]
• Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast RatesNicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaïd Harchaoui. 10161-10195 [doi]
• Solving Marginal MAP Exactly by Probabilistic Circuit TransformationsYoojung Choi, Tal Friedman, Guy Van den Broeck. 10196-10208 [doi]
• REPID: Regional Effect Plots with implicit Interaction DetectionJulia Herbinger, Bernd Bischl, Giuseppe Casalicchio. 10209-10233 [doi]
• Minimal Expected Regret in Linear Quadratic ControlYassir Jedra, Alexandre Proutière. 10234-10321 [doi]
• Data-splitting improves statistical performance in overparameterized regimesNicole Mücke, Enrico Reiss, Jonas Rungenhagen, Markus Klein. 10322-10350 [doi]
• Towards Understanding Biased Client Selection in Federated LearningYae Jee Cho, Jianyu Wang, Gauri Joshi. 10351-10375 [doi]
• Statistical Depth Functions for Ranking Distributions: Definitions, Statistical Learning and ApplicationsMorgane Goibert, Stéphan Clémençon, Ekhine Irurozki, Pavlo Mozharovskyi. 10376-10406 [doi]
• Effective Nonlinear Feature Selection Method based on HSIC Lasso and with Variational InferenceKazuki Koyama, Keisuke Kiritoshi, Tomomi Okawachi, Tomonori Izumitani. 10407-10421 [doi]
• Sobolev Norm Learning Rates for Conditional Mean EmbeddingsPrem Talwai, Ali Shameli, David Simchi-Levi. 10422-10447 [doi]
• Provable Continual Learning via Sketched Jacobian ApproximationsReinhard Heckel. 10448-10470 [doi]
• Neural Enhanced Dynamic Message PassingFei Gao, Jiang Zhang, Yan Zhang. 10471-10482 [doi]
• Duel-based Deep Learning system for solving IQ testsPaulina Tomaszewska, Adam Zychowski, Jacek Mandziuk. 10483-10492 [doi]
• On a Connection Between Fast and Sparse Oblivious Subspace EmbeddingsRui Wang, Wangli Xu. 10493-10517 [doi]
• Modeling Conditional Dependencies in Multiagent TrajectoriesYannick Rudolph, Ulf Brefeld. 10518-10533 [doi]
• Testing Granger Non-Causality in Panels with Cross-Sectional DependenciesLenon Minorics, Ali Caner Türkmen, David Kernert, Patrick Blöbaum, Laurent Callot, Dominik Janzing. 10534-10554 [doi]
• Increasing the accuracy and resolution of precipitation forecasts using deep generative modelsIlan Price, Stephan Rasp 0001. 10555-10571 [doi]
• 1-norm interpolation of noisy dataGuillaume Wang, Konstantin Donhauser, Fanny Yang. 10572-10602 [doi]
• Multivariate Quantile Function ForecasterKelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus. 10603-10621 [doi]
• Coresets for Data Discretization and Sine Wave FittingAlaa Maalouf, Murad Tukan, Eric Price 0001, Daniel M. Kane, Dan Feldman. 10622-10639 [doi]
• Non-separable Spatio-temporal Graph Kernels via SPDEsAlexander V. Nikitin, St John, Arno Solin, Samuel Kaski. 10640-10660 [doi]
• Towards an Understanding of Default Policies in Multitask Policy OptimizationTed Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano. 10661-10686 [doi]
• Multiple Importance Sampling ELBO and Deep Ensembles of Variational ApproximationsOskar Kviman, Harald Melin, Hazal Koptagel, Victor Elvira, Jens Lagergren. 10687-10702 [doi]
• Can Functional Transfer Methods Capture Simple Inductive Biases?Arne Nix, Suhas Shrinivasan, Edgar Y. Walker, Fabian H. Sinz. 10703-10717 [doi]
• On the Oracle Complexity of Higher-Order Smooth Non-Convex Finite-Sum OptimizationNicolas Emmenegger, Rasmus Kyng, Ahad N. Zehmakan. 10718-10752 [doi]
• Model-agnostic out-of-distribution detection using combined statistical testsFederico Bergamin, Pierre-Alexandre Mattei, Jakob Drachmann Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen. 10753-10776 [doi]
• Generalized Group TestingXiwei Cheng, Sidharth Jaggi, Qiaoqiao Zhou. 10777-10835 [doi]
• Adaptive A/B Test on Networks with Cluster StructuresYang Liu, Yifan Zhou, Ping Li, Feifang Hu. 10836-10851 [doi]
• Spectral Robustness for Correlation Clustering Reconstruction in Semi-Adversarial ModelsFlavio Chierichetti, Alessandro Panconesi, Giuseppe Re, Luca Trevisan. 10852-10880 [doi]
• Beyond Data Samples: Aligning Differential Networks Estimation with Scientific KnowledgeArshdeep Sekhon, Zhe Wang, Yanjun Qi. 10881-10923 [doi]
• Two-way Sparse Network Inference for Count DataSijia Li, Martín López-García, Neil D. Lawrence, Luisa Cutillo. 10924-10938 [doi]
• Rapid Convergence of Informed Importance TemperingQuan Zhou, Aaron Smith. 10939-10965 [doi]
• On the Implicit Bias of Gradient Descent for Temporal ExtrapolationEdo Cohen-Karlik, Avichai Ben David, Nadav Cohen, Amir Globerson. 10966-10981 [doi]
• Differentiable Bayesian inference of SDE parameters using a pathwise series expansion of Brownian motionSanmitra Ghosh, Paul J. Birrell, Daniela De Angelis. 10982-10998 [doi]
• Quadric Hypersurface Intersection for Manifold Learning in Feature SpaceFedor Pavutnitskiy, Sergei O. Ivanov, Evgeniy Abramov, Viacheslav Borovitskiy, Artem Klochkov, Viktor Vyalov, Anatolii Zaikovskii, Aleksandr Petiushko. 10999-11013 [doi]
• Adaptive Sampling for Heterogeneous Rank Aggregation from Noisy Pairwise ComparisonsYue Wu, Tao Jin, Hao Lou, Pan Xu 0002, Farzad Farnoud, Quanquan Gu. 11014-11036 [doi]
• Outcome Assumptions and Duality Theory for Balancing WeightsDavid A. Bruns-Smith, Avi Feller. 11037-11055 [doi]
• Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approachSetareh Ariafar, Justin Gilmer, Zachary Nado, Jasper Snoek, Rodolphe Jenatton, George E. Dahl. 11056-11071 [doi]
• Learning from Multiple Noisy Partial LabelersPeilin Yu, Tiffany Ding, Stephen H. Bach. 11072-11095 [doi]
• Forward Looking Best-Response Multiplicative Weights Update Methods for Bilinear Zero-sum GamesMichail Fasoulakis, Evangelos Markakis, Yannis Pantazis, Constantinos Varsos. 11096-11117 [doi]
• Hypergraph Simultaneous GeneratorsBahman Pedrood, Carlotta Domeniconi, Kathryn B. Laskey. 11118-11130 [doi]
• Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio EstimationJoel Dyer, Patrick W. Cannon, Sebastian M. Schmon. 11131-11144 [doi]
• Robust Training in High Dimensions via Block Coordinate Geometric Median DescentAnish Acharya, Abolfazl Hashemi, Prateek Jain 0002, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu. 11145-11168 [doi]
• Stateful Offline Contextual Policy Evaluation and LearningNathan Kallus, Angela Zhou. 11169-11194 [doi]
• Sample Complexity of Policy-Based Methods under Off-Policy Sampling and Linear Function ApproximationZaiwei Chen, Siva Theja Maguluri. 11195-11214 [doi]
• Solving Multi-Arm Bandit Using a Few Bits of CommunicationOsama A. Hanna, Lin Yang 0011, Christina Fragouli. 11215-11236 [doi]
• Causal Effect Identification with Context-specific Independence Relations of Control VariablesEhsan Mokhtarian, Fateme Jamshidi, Jalal Etesami, Negar Kiyavash. 11237-11246 [doi]
• Entropy Regularized Optimal Transport Independence CriterionLang Liu, Soumik Pal, Zaïd Harchaoui. 11247-11279 [doi]
• Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value FunctionsZihao Deng, Siddartha Devic, Brendan Juba. 11280-11304 [doi]
• PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal ConsistencyArun Padakandla, Abram Magner. 11305-11319 [doi]
• Can we Generalize and Distribute Private Representation Learning?Sheikh Shams Azam, Taejin Kim, Seyyedali Hosseinalipour, Carlee Joe-Wong, Saurabh Bagchi, Christopher G. Brinton. 11320-11340 [doi]
• Feature Collapsing for Gaussian Process Variable RankingIsaac Sebenius, Topi Paananen, Aki Vehtari. 11341-11355 [doi]
• Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample SizeWanrong Zhang 0001, Yajun Mei, Rachel Cummings. 11356-11373 [doi]
• FLIX: A Simple and Communication-Efficient Alternative to Local Methods in Federated LearningElnur Gasanov, Ahmed Khaled 0001, Samuel Horváth, Peter Richtárik. 11374-11421 [doi]
• Data Appraisal Without Data SharingXinlei Xu, Awni Y. Hannun, Laurens van der Maaten. 11422-11437 [doi]
• On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed BoundsTrung Le, Anh Tuan Bui, Le Minh Tri Tue, He Zhao 0001, Paul Montague, Quan Hung Tran, Dinh Q. Phung. 11438-11460 [doi]
• Transductive Robust Learning GuaranteesOmar Montasser, Steve Hanneke, Nathan Srebro. 11461-11471 [doi]
• Online Competitive Influence MaximizationJinhang Zuo, Xutong Liu 0002, Carlee Joe-Wong, John C. S. Lui, Wei Chen 0013. 11472-11502 [doi]
• Adaptive Importance Sampling meets Mirror Descent : a Bias-variance TradeoffAnna Korba, François Portier. 11503-11527 [doi]
• The role of optimization geometry in single neuron learningNicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine. 11528-11549 [doi]
• Learning Tensor Representations for Meta-LearningSamuel Deng, Yilin Guo, Daniel Hsu 0001, Debmalya Mandal. 11550-11580 [doi]
• Differentially Private Densest SubgraphAlireza Farhadi 0001, Mohammad Taghi Hajiaghai, Elaine Shi. 11581-11597 [doi]
• A Manifold View of Adversarial RiskWenJia Zhang, Yikai Zhang, Xiaoling Hu 0002, Mayank Goswami 0001, Chao Chen 0012, Dimitris N. Metaxas. 11598-11614 [doi]
• Statistical and computational thresholds for the planted k-densest sub-hypergraph problemLuca Corinzia, Paolo Penna, Wojciech Szpankowski, Joachim M. Buhmann. 11615-11640 [doi]
• Controlling Epidemic Spread using Probabilistic Diffusion Models on NetworksAmy E. Babay, Michael Dinitz, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti. 11641-11654 [doi]
• Equivariant Deep Dynamical Model for Motion PredictionBahar Azari, Deniz Erdogmus. 11655-11668 [doi]
• The Fast Kernel TransformJohn Paul Ryan, Sebastian E. Ament, Carla P. Gomes, Anil Damle. 11669-11690 [doi]
• Outlier-Robust Optimal Transport: Duality, Structure, and Statistical AnalysisSloan Nietert, Ziv Goldfeld, Rachel Cummings. 11691-11719 [doi]
• Diversity and Generalization in Neural Network EnsemblesLuis A. Ortega, Rafael Cabañas, Andrés R. Masegosa. 11720-11743 [doi]