Table of Contents

• Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank ApproximationShinsaku Sakaue, Taihei Oki. 1-10 [doi]
• Meta-Uncertainty in Bayesian Model ComparisonMarvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner. 11-29 [doi]
• PAC Learning of Halfspaces with Malicious Noise in Nearly Linear TimeJie Shen. 30-46 [doi]
• Entropic Risk Optimization in Discounted MDPsJia Lin Hau, Marek Petrik, Mohammad Ghavamzadeh. 47-76 [doi]
• Acceleration of Frank-Wolfe Algorithms with Open-Loop Step-SizesElias Samuel Wirth, Thomas Kerdreux, Sebastian Pokutta. 77-100 [doi]
• An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk MinimizationLianke Qin, Zhao Song 0002, Lichen Zhang 0003, Danyang Zhuo. 101-156 [doi]
• Leveraging Instance Features for Label Aggregation in Programmatic Weak SupervisionJieyu Zhang, Linxin Song, Alex Ratner. 157-171 [doi]
• Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient MethodsAleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou. 172-235 [doi]
• Scalable marked point processes for exchangeable and non-exchangeable event sequencesAristeidis Panos, Ioannis Kosmidis, Petros Dellaportas. 236-252 [doi]
• Bayesian Variable Selection in a Million DimensionsMartin Jankowiak. 253-282 [doi]
• Blessing of Class Diversity in Pre-trainingYulai Zhao 0002, Jianshu Chen, Simon S. Du. 283-305 [doi]
• Barlow Graph Auto-Encoder for Unsupervised Network EmbeddingRayyan Ahmad Khan, Martin Kleinsteuber. 306-322 [doi]
• Gradient-Informed Neural Network Statistical Robustness EstimationKarim Tit, Teddy Furon, Mathias Rousset. 323-334 [doi]
• Online Defense Strategies for Reinforcement Learning Against Adaptive Reward PoisoningAndi Nika, Adish Singla, Goran Radanovic. 335-358 [doi]
• A Case of Exponential Convergence Rates for SVMVivien Cabannes, Stefano Vigogna. 359-374 [doi]
• Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement LearningRuitu Xu, Yifei Min, Tianhao Wang 0002, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang. 375-407 [doi]
• Adaptive Cholesky Gaussian ProcessesSimon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Muñoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg. 408-452 [doi]
• Sample Complexity of Kernel-Based Q-LearningSing-Yuan Yeh, Fu-Chieh Chang 0001, Chang-Wei Yueh, Pei Yuan Wu, Alberto Bernacchia, Sattar Vakili. 453-469 [doi]
• A principled framework for the design and analysis of token algorithmsHadrien Hendrikx. 470-489 [doi]
• Learning k-qubit Quantum Operators via Pauli DecompositionMohsen Heidari, Wojciech Szpankowski. 490-504 [doi]
• Semi-Verified PAC Learning from the CrowdShiwei Zeng, Jie Shen 0005. 505-522 [doi]
• On the Capacity Limits of Privileged ERMMichal Sharoni, Sivan Sabato. 523-534 [doi]
• USIM Gate: UpSampling Module for Segmenting Precise Boundaries concerning EntropyKyungsu Lee, Haeyun Lee, Jae Youn Hwang. 535-562 [doi]
• Bayesian Structure Scores for Probabilistic CircuitsYang Yang, Gennaro Gala, Robert Peharz. 563-575 [doi]
• Langevin Diffusion Variational InferenceTomas Geffner, Justin Domke. 576-593 [doi]
• Overcoming Prior Misspecification in Online Learning to RankJavad Azizi, Ofer Meshi, Masrour Zoghi, Maryam Karimzadehgan. 594-614 [doi]
• Catalyst Acceleration of Error Compensated Methods Leads to Better Communication ComplexityXun Qian, Hanze Dong, Tong Zhang, Peter Richtárik. 615-649 [doi]
• Kernel Conditional Moment Constraints for Confounding Robust InferenceKei Ishikawa, Niao He. 650-674 [doi]
• Meta-learning for Robust Anomaly DetectionAtsutoshi Kumagai, Tomoharu Iwata, Hiroshi Takahashi, Yasuhiro Fujiwara. 675-691 [doi]
• Learning in RKHM: a C*-Algebraic Twist for Kernel MachinesYuka Hashimoto, Masahiro Ikeda, Hachem Kadri. 692-708 [doi]
• From Shapley Values to Generalized Additive Models and backSebastian Bordt, Ulrike von Luxburg. 709-745 [doi]
• Estimating Conditional Average Treatment Effects with Missing Treatment InformationMilan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel. 746-766 [doi]
• Global Convergence of Over-parameterized Deep Equilibrium ModelsZenan Ling, Xingyu Xie, Qiuhao Wang, Zongpeng Zhang, Zhouchen Lin. 767-787 [doi]
• A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action SpaceZhaozhuo Xu, Zhao Song 0002, Anshumali Shrivastava. 788-836 [doi]
• Adversarial De-confounding in Individualised Treatment Effects EstimationVinod Kumar Chauhan, Soheila Molaei, Marzia Hoque Tania, Anshul Thakur, Tingting Zhu 0001, David A. Clifton. 837-849 [doi]
• Fast Distributed k-Means with a Small Number of RoundsTom Hess, Ron Visbord, Sivan Sabato. 850-874 [doi]
• A New Causal Decomposition Paradigm towards Health EquityXinwei Sun 0001, Xiangyu Zheng, Jim Weinstein. 875-890 [doi]
• Matching Map Recovery with an Unknown Number of OutliersArshak Minasyan, Tigran Galstyan, Sona Hunanyan, Arnak S. Dalalyan. 891-906 [doi]
• Characterizing Internal Evasion Attacks in Federated LearningTaejin Kim, Shubhranshu Singh, Nikhil Madaan, Carlee Joe-Wong. 907-921 [doi]
• Optimal and Private Learning from Human Response DataDuc Nguyen, Anderson Ye Zhang. 922-958 [doi]
• Bayesian Optimization with Conformal Prediction SetsSamuel Stanton, Wesley J. Maddox, Andrew Gordon Wilson. 959-986 [doi]
• Alternating Projected SGD for Equality-constrained Bilevel OptimizationQuan Xiao, Han Shen, Wotao Yin, Tianyi Chen. 987-1023 [doi]
• Improved Robust Algorithms for Learning with Discriminative Feature FeedbackSivan Sabato. 1024-1036 [doi]
• Weisfeiler and Leman go Hyperbolic: Learning Distance Preserving Node RepresentationsGiannis Nikolentzos, Michail Chatzianastasis, Michalis Vazirgiannis. 1037-1054 [doi]
• Can 5th Generation Local Training Methods Support Client Sampling? Yes!Michal Grudzien, Grigory Malinovsky, Peter Richtárik. 1055-1092 [doi]
• qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian OptimizationRaul Astudillo, Zhiyuan (Jerry) Lin, Eytan Bakshy, Peter I. Frazier. 1093-1114 [doi]
• Bayesian Hierarchical Models for Counterfactual EstimationNatraj Raman, Daniele Magazzeni, Sameena Shah. 1115-1128 [doi]
• Sequential Gradient Descent and Quasi-Newton's Method for Change-Point AnalysisXianyang Zhang, Trisha Dawn. 1129-1143 [doi]
• Towards Scalable and Robust Structured Bandits: A Meta-Learning FrameworkRunzhe Wan, Lin Ge, Rui Song 0006. 1144-1173 [doi]
• Compress Then Test: Powerful Kernel Testing in Near-linear TimeCarles Domingo-Enrich, Raaz Dwivedi, Lester Mackey. 1174-1218 [doi]
• Select and Optimize: Learning to aolve large-scale TSP instancesHanni Cheng, Haosi Zheng, Ya Cong, Weihao Jiang, Shiliang Pu. 1219-1231 [doi]
• Fixing by Mixing: A Recipe for Optimal Byzantine ML under HeterogeneityYoussef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan. 1232-1300 [doi]
• Testing of Horn SamplersAnsuman Banerjee, Shayak Chakraborty, Sourav Chakraborty 0001, Kuldeep S. Meel, Uddalok Sarkar, Sayantan Sen. 1301-1330 [doi]
• Coordinate Ascent for Off-Policy RL with Global Convergence GuaranteesHsin-En Su, Yen-Ju Chen, Ping-Chun Hsieh, Xi Liu 0011. 1331-1378 [doi]
• Positional Encoder Graph Neural Networks for Geographic DataKonstantin Klemmer, Nathan S. Safir, Daniel B. Neill. 1379-1389 [doi]
• Coarse-Grained Smoothness for Reinforcement Learning in Metric SpacesOmer Gottesman, Kavosh Asadi, Cameron S. Allen, Samuel Lobel, George Konidaris 0001, Michael L. Littman. 1390-1410 [doi]
• BaCaDI: Bayesian Causal Discovery with Unknown InterventionsAlexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause 0001. 1411-1436 [doi]
• Statistical Analysis of Karcher Means for Random Restricted PSD MatricesHengchao Chen, Xiang Li, Qiang Sun. 1437-1456 [doi]
• Differentially Private Synthetic ControlSaeyoung Rho, Rachel Cummings, Vishal Misra. 1457-1491 [doi]
• Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian ProcessesFelix Jimenez, Matthias Katzfuss. 1492-1512 [doi]
• On the Neural Tangent Kernel Analysis of Randomly Pruned Neural NetworksHongru Yang, Zhangyang Wang. 1513-1553 [doi]
• Riemannian Accelerated Gradient Methods via ExtrapolationAndi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao. 1554-1585 [doi]
• Flexible risk design using bi-directional dispersionMatthew J. Holland. 1586-1623 [doi]
• Contextual Linear Bandits under Noisy Features: Towards Bayesian OraclesJung Hun Kim, Se-Young Yun, Minchan Jeong, Junhyun Nam, Jinwoo Shin, Richard Combes. 1624-1645 [doi]
• Deep equilibrium models as estimators for continuous latent variablesRussell Tsuchida, Cheng Soon Ong. 1646-1671 [doi]
• Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous DataBatiste Le Bars, Aurélien Bellet, Marc Tommasi, Erick Lavoie, Anne-Marie Kermarrec. 1672-1702 [doi]
• A Novel Stochastic Gradient Descent Algorithm for Learning Principal SubspacesCharline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare. 1703-1718 [doi]
• A Constant-Factor Approximation Algorithm for Reconciliation k-MedianJoachim Spoerhase, Kamyar Khodamoradi, Benedikt Riegel, Bruno Ordozgoiti, Aristides Gionis. 1719-1746 [doi]
• Neural Laplace Control for Continuous-time Delayed SystemsSamuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar. 1747-1778 [doi]
• Discovering Many Diverse Solutions with Bayesian OptimizationNatalie Maus, Kaiwen Wu, David Eriksson, Jacob R. Gardner. 1779-1798 [doi]
• BlitzMask: Real-Time Instance Segmentation Approach for Mobile DevicesVitalii Bulygin, Dmytro Mykheievskyi, Kyrylo Kuchynskyi. 1799-1811 [doi]
• Exact Gradient Computation for Spiking Neural Networks via Forward PropagationJane H. Lee, Saeid Haghighatshoar, Amin Karbasi. 1812-1831 [doi]
• Uni6Dv2: Noise Elimination for 6D Pose EstimationMingshan Sun, Ye Zheng, Tianpeng Bao, Jianqiu Chen, Guoqiang Jin, Liwei Wu, Rui Zhao, Xiaoke Jiang. 1832-1844 [doi]
• Multilevel Bayesian QuadratureKaiyu Li, Daniel Giles, Toni Karvonen, Serge Guillas, François-Xavier Briol. 1845-1868 [doi]
• Direct Inference of Effect of Treatment (DIET) for a Cookieless WorldShiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Madalina Fiterau. 1869-1887 [doi]
• The Ordered Matrix Dirichlet for State-Space ModelsNiklas Stoehr, Benjamin J. Radford, Ryan Cotterell, Aaron Schein. 1888-1903 [doi]
• Energy-Based Models for Functional Data using Path Measure TiltingJen Ning Lim, Sebastian J. Vollmer, Lorenz Wolf, Andrew Duncan. 1904-1923 [doi]
• Frequentist Uncertainty Quantification in Semi-Structured Neural NetworksEmilio Dorigatti, Benjamin Schubert, Bernd Bischl, David Rügamer. 1924-1941 [doi]
• NTS-NOTEARS: Learning Nonparametric DBNs With Prior KnowledgeXiangyu Sun, Oliver Schulte, Guiliang Liu, Pascal Poupart. 1942-1964 [doi]
• One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement LearningPedro Cisneros-Velarde, Boxiang Lyu, Sanmi Koyejo, Mladen Kolar. 1965-2001 [doi]
• Variational Inference for Neyman-Scott ProcessesChengkuan Hong, Christian R. Shelton. 2002-2018 [doi]
• Graph Alignment Kernels using Weisfeiler and Leman HierarchiesGiannis Nikolentzos, Michalis Vazirgiannis. 2019-2034 [doi]
• Geometric Random Walk Graph Neural Networks via Implicit LayersGiannis Nikolentzos, Michalis Vazirgiannis. 2035-2053 [doi]
• Model-X Sequential Testing for Conditional Independence via Testing by BettingShalev Shaer, Gal Maman, Yaniv Romano. 2054-2086 [doi]
• Mixed-Effect Thompson SamplingImad Aouali, Branislav Kveton, Sumeet Katariya. 2087-2115 [doi]
• Mixed Linear Regression via Approximate Message PassingNelvin Tan, Ramji Venkataramanan. 2116-2131 [doi]
• EEGNN: Edge Enhanced Graph Neural Network with a Bayesian Nonparametric Graph ModelYirui Liu, Xinghao Qiao, Liying Wang, Jessica Lam. 2132-2146 [doi]
• Estimating Total Correlation with Mutual Information EstimatorsKe Bai, Pengyu Cheng, Weituo Hao, Ricardo Henao, Larry Carin. 2147-2164 [doi]
• Vector Optimization with Stochastic Bandit FeedbackÇagin Ararat, Cem Tekin. 2165-2190 [doi]
• Knowledge Acquisition for Human-In-The-Loop Image CaptioningErvine Zheng, Qi Yu 0001, Rui Li 0002, Pengcheng Shi, Anne R. Haake. 2191-2206 [doi]
• A Statistical Analysis of Polyak-Ruppert Averaged Q-LearningXiang Li, Wenhao Yang, Jiadong Liang, Zhihua Zhang, Michael I. Jordan. 2207-2261 [doi]
• Linear Convergence of Gradient Descent For Finite Width Over-parametrized Linear Networks With General InitializationZiqing Xu, Hancheng Min, Salma Tarmoun, Enrique Mallada, René Vidal. 2262-2284 [doi]
• "Plus/minus the learning rate": Easy and Scalable Statistical Inference with SGDJerry Chee, Hwanwoo Kim, Panos Toulis. 2285-2309 [doi]
• Distance-to-Set Priors and Constrained Bayesian InferenceRick Presman, Jason Xu. 2310-2326 [doi]
• Fast Computation of Branching Process Transition Probabilities via ADMMAchal Awasthi, Jason Xu. 2327-2347 [doi]
• Error Estimation for Random Fourier FeaturesJunwen Yao, N. Benjamin Erichson, Miles E. Lopes. 2348-2364 [doi]
• AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax OptimizationFeihu Huang, Xidong Wu, Zhengmian Hu. 2365-2389 [doi]
• Classification of Adolescents' Risky Behavior in Instant Messaging ConversationsJaromír Plhák, Ondrej Sotolár, Michaela Lebedíková, David Smahel. 2390-2404 [doi]
• Robust Linear Regression for General Feature DistributionTom Norman, Nir Weinberger, Kfir Y. Levy. 2405-2435 [doi]
• Fair learning with Wasserstein barycenters for non-decomposable performance measuresSolenne Gaucher, Nicolas Schreuder, Evgenii Chzhen. 2436-2459 [doi]
• Deep Neural Networks with Efficient Guaranteed InvariancesMatthias Rath 0001, Alexandru Paul Condurache. 2460-2480 [doi]
• Fast Block Coordinate Descent for Non-Convex Group RegularizationsYasutoshi Ida, Sekitoshi Kanai, Atsutoshi Kumagai. 2481-2493 [doi]
• AUC-based Selective ClassificationAndrea Pugnana, Salvatore Ruggieri. 2494-2514 [doi]
• Nonparametric Indirect Active LearningShashank Singh 0011. 2515-2541 [doi]
• Resolving the Approximability of Offline and Online Non-monotone DR-Submodular Maximization over General Convex SetsLoay Mualem, Moran Feldman. 2542-2564 [doi]
• 2ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian OptimizationJixiang Qing, Henry B. Moss, Tom Dhaene, Ivo Couckuyt. 2565-2588 [doi]
• Learning Constrained Structured Spaces with Application to Multi-Graph MatchingHedda Cohen Indelman, Tamir Hazan. 2589-2602 [doi]
• On the Strategyproofness of the Geometric MedianEl Mahdi El Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Lê Nguyên Hoang. 2603-2640 [doi]
• Covariate-informed Representation Learning to Prevent Posterior Collapse of iVAEYoung-geun Kim, Ying Liu, Xuexin Wei. 2641-2660 [doi]
• EGG-GAE: scalable graph neural networks for tabular data imputationLev Telyatnikov, Simone Scardapane. 2661-2676 [doi]
• Group Distributionally Robust Reinforcement Learning with Hierarchical Latent VariablesMengdi Xu, Peide Huang, Yaru Niu, Visak Kumar, Jielin Qiu, Chao Fang, Kuan-Hui Lee, Xuewei Qi, Henry Lam, Bo Li, Ding Zhao. 2677-2703 [doi]
• Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather StationsXun Zhu, Yutong Xiong, Ming Wu, Gaozhen Nie, Bin Zhang, Ziheng Yang. 2704-2722 [doi]
• Improved Rate of First Order Algorithms for Entropic Optimal TransportYiling Luo, Yiling Xie, Xiaoming Huo. 2723-2750 [doi]
• Conformal Off-Policy PredictionYingying Zhang, Chengchun Shi, Shikai Luo. 2751-2768 [doi]
• Sparse Spectral Bayesian Permanental Process with Generalized KernelJeremy Sellier, Petros Dellaportas. 2769-2791 [doi]
• Adversarial Noises Are Linearly Separable for (Nearly) Random Neural NetworksHuishuai Zhang, Da Yu, Yiping Lu, Di He. 2792-2804 [doi]
• Nearly Optimal Latent State Decoding in Block MDPsYassir Jedra, Junghyun Lee, Alexandre Proutière, Se-Young Yun. 2805-2904 [doi]
• On the Limitations of the Elo, Real-World Games are Transitive, not AdditiveQuentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel. 2905-2921 [doi]
• 2-Polynomial RegressionMohsen Heidari, Wojciech Szpankowski. 2922-2938 [doi]
• Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation GroupZhenbang Wang, Emanuel Ben-David, Martin Slawski. 2939-2959 [doi]
• Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse ProblemsLuca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee. 2960-2974 [doi]
• Analysis of Catastrophic Forgetting for Random Orthogonal Transformation Tasks in the Overparameterized RegimeDaniel Goldfarb, Paul Hand. 2975-2993 [doi]
• Clustering above Exponential Families with Tempered Exponential MeasuresEhsan Amid, Richard Nock, Manfred K. Warmuth. 2994-3017 [doi]
• Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial NetsHussein Hazimeh 0001, Natalia Ponomareva. 3018-3033 [doi]
• Learning Physics-Informed Neural Networks without Stacked Back-propagationDi He, Shanda Li, Wenlei Shi, Xiaotian Gao, Jia Zhang, Jiang Bian 0002, Liwei Wang, Tie-Yan Liu. 3034-3047 [doi]
• An Optimization-based Algorithm for Non-stationary Kernel Bandits without Prior KnowledgeKihyuk Hong, Yuhang Li, Ambuj Tewari. 3048-3085 [doi]
• Multi-armed Bandit Experimental Design: Online Decision-making and Adaptive InferenceDavid Simchi-Levi, Chonghuan Wang. 3086-3097 [doi]
• Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual BanditsWonyoung Kim, Myunghee Cho Paik, Min-hwan Oh. 3098-3124 [doi]
• Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence RateZiye Ma, Somayeh Sojoudi. 3125-3150 [doi]
• Byzantine-Robust Federated Learning with Optimal Statistical RatesBanghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan. 3151-3178 [doi]
• An Unpooling Layer for Graph GenerationYinglong Guo, Dongmian Zou, Gilad Lerman. 3179-3209 [doi]
• Online Learning for Traffic Routing under Unknown PreferencesDevansh Jalota, Karthik Gopalakrishnan 0002, Navid Azizan, Ramesh Johari, Marco Pavone 0001. 3210-3229 [doi]
• Byzantine-Robust Online and Offline Distributed Reinforcement LearningYiding Chen, Xuezhou Zhang, Kaiqing Zhang, Mengdi Wang, Xiaojin Zhu 0001. 3230-3269 [doi]
• No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand DistributionMengxiao Zhang, Shi Chen, Haipeng Luo, Yingfei Wang. 3270-3298 [doi]
• Mode-constrained Model-based Reinforcement Learning via Gaussian ProcessesAidan Scannell, Carl Henrik Ek, Arthur Richards. 3299-3314 [doi]
• Generative Oversampling for Imbalanced Data via Majority-Guided VAEQingzhong Ai, Pengyun Wang, Lirong He, Liangjian Wen, Lujia Pan, Zenglin Xu. 3315-3330 [doi]
• The Lie-Group Bayesian Learning RuleEren Mehmet Kiral, Thomas Möllenhoff, Mohammad Emtiyaz Khan. 3331-3352 [doi]
• Singular Value Representation: A New Graph Perspective On Neural NetworksDan Meller, Nicolas Berkouk. 3353-3369 [doi]
• A Finite Sample Complexity Bound for Distributionally Robust Q-learningShengbo Wang, Nian Si, José H. Blanchet, Zhengyuan Zhou. 3370-3398 [doi]
• Connectivity-contrastive learning: Combining causal discovery and representation learning for multimodal dataHiroshi Morioka, Aapo Hyvärinen. 3399-3426 [doi]
• A Bregman Divergence View on the Difference-of-Convex AlgorithmOisin Faust, Hamza Fawzi, James Saunderson. 3427-3439 [doi]
• Minority Oversampling for Imbalanced Data via Class-Preserving Regularized Auto-EncodersArnab Kumar Mondal, Lakshya Singhal, Piyush Tiwary, Parag Singla, Prathosh AP. 3440-3465 [doi]
• T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease ProgressionYuchao Qin, Mihaela van der Schaar, ChangHee Lee. 3466-3492 [doi]
• Membership Inference Attacks against Synthetic Data through Overfitting DetectionBoris van Breugel, Hao Sun, Zhaozhi Qian, Mihaela van der Schaar. 3493-3514 [doi]
• Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit FeedbackQixin Zhang, Zengde Deng, Zaiyi Chen, Kuangqi Zhou, Haoyuan Hu, Yu Yang 0001. 3515-3537 [doi]
• Robust Variational Autoencoding with Wasserstein Penalty for Novelty DetectionChieh-Hsin Lai, Dongmian Zou, Gilad Lerman. 3538-3567 [doi]
• To Impute or not to Impute? Missing Data in Treatment Effect EstimationJeroen Berrevoets, Fergus Imrie, Trent Kyono, James Jordon, Mihaela van der Schaar. 3568-3590 [doi]
• No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown UtilitiesSebastian Shenghong Tay, Quoc Phong Nguyen, Chuan-Sheng Foo, Bryan Kian Hsiang Low. 3591-3619 [doi]
• Noise-Aware Statistical Inference with Differentially Private Synthetic DataOssi Räisä, Joonas Jälkö, Samuel Kaski, Antti Honkela. 3620-3643 [doi]
• ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural NetworksLouis Leconte, Sholom Schechtman, Eric Moulines. 3644-3663 [doi]
• Transport Elliptical Slice SamplingAlberto Cabezas, Christopher Nemeth. 3664-3676 [doi]
• Towards Balanced Representation Learning for Credit Policy EvaluationYiyan Huang, Cheuk Hang Leung, Shumin Ma, Zhiri Yuan, Qi Wu 0009, Siyi Wang, Dongdong Wang, Zhixiang Huang. 3677-3692 [doi]
• Convergence of Stein Variational Gradient Descent under a Weaker Smoothness ConditionLukang Sun, Avetik G. Karagulyan, Peter Richtárik. 3693-3717 [doi]
• MARS: Masked Automatic Ranks Selection in Tensor DecompositionsMaxim Kodryan, Dmitry Kropotov, Dmitry P. Vetrov. 3718-3732 [doi]
• Learning from Multiple Sources for Data-to-Text and Text-to-DataSong Duong, Alberto Lumbreras, Mike Gartrell, Patrick Gallinari. 3733-3753 [doi]
• Sparse Bayesian optimizationSulin Liu, Qing Feng, David Eriksson, Benjamin Letham, Eytan Bakshy. 3754-3774 [doi]
• On the bias of K-fold cross validation with stable learnersAnass Aghbalou, Anne Sabourin, François Portier. 3775-3794 [doi]
• Bayesian Convolutional Deep Sets with Task-Dependent Stationary PriorYohan Jung, Jinkyoo Park. 3795-3824 [doi]
• Sample Efficiency of Data Augmentation Consistency RegularizationShuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei. 3825-3853 [doi]
• ANACONDA: An Improved Dynamic Regret Algorithm for Adaptive Non-Stationary Dueling BanditsThomas Kleine Buening, Aadirupa Saha. 3854-3878 [doi]
• Deep Joint Source-Channel Coding with Iterative Source Error CorrectionChangwoo Lee, Xiao Hu, Hun-Seok Kim. 3879-3902 [doi]
• On-Demand Communication for Asynchronous Multi-Agent BanditsYu-Zhen Janice Chen, Lin Yang, Xuchuang Wang, Xutong Liu 0002, Mohammad H. Hajiesmaili, John C. S. Lui, Don Towsley. 3903-3930 [doi]
• The ELBO of Variational Autoencoders Converges to a Sum of EntropiesSimon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke. 3931-3960 [doi]
• Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment BatteryJoshua C. Chang, Carson C. Chow, Julia Porcino. 3961-3976 [doi]
• Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential PrivacyRachel Redberg, Yuqing Zhu 0005, Yu-Xiang Wang 0003. 3977-4005 [doi]
• Provably Efficient Reinforcement Learning via Surprise BoundHanlin Zhu, Ruosong Wang, Jason D. Lee. 4006-4032 [doi]
• FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific DiscoveryXinyi Xu, Zhaoxuan Wu, Arun Verma, Chuan-Sheng Foo, Bryan Kian Hsiang Low. 4033-4057 [doi]
• Sampling From a Schrödinger BridgeAustin J. Stromme. 4058-4067 [doi]
• A Multi-Task Gaussian Process Model for Inferring Time-Varying Treatment Effects in Panel DataYehu Chen, Annamaria Prati, Jacob M. Montgomery, Roman Garnett. 4068-4088 [doi]
• Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven ModelsNaoya Takeishi, Alexandros Kalousis. 4089-4100 [doi]
• Active Learning for Single Neuron Models with Lipschitz Non-LinearitiesAarshvi Gajjar, Christopher Musco, Chinmay Hegde. 4101-4113 [doi]
• Exploration in Reward Machines with Low RegretHippolyte Bourel, Anders Jonsson, Odalric-Ambrym Maillard, Mohammad Sadegh Talebi. 4114-4146 [doi]
• On Universal Portfolios with Continuous Side InformationAlankrita Bhatt, J. Jon Ryu, Young-Han Kim 0001. 4147-4163 [doi]
• Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image RepresentationYaxuan Zhu, Jianwen Xie, Ping Li. 4164-4180 [doi]
• The Lauritzen-Chen Likelihood For Graphical ModelsIlya Shpitser. 4181-4195 [doi]
• Bayesian Strategy-Proof Facility Location via Robust EstimationEmmanouil Zampetakis, Fred Zhang. 4196-4208 [doi]
• Unsupervised representation learning with recognition-parametrised probabilistic modelsWilliam I. Walker, Hugo Soulat, Changmin Yu, Maneesh Sahani. 4209-4230 [doi]
• Universal Agent Mixtures and the Geometry of IntelligenceSamuel Allen Alexander, David Quarel, Len Du, Marcus Hutter. 4231-4246 [doi]
• The communication cost of security and privacy in federated frequency estimationWei-Ning Chen, Ayfer Özgür, Graham Cormode, Akash Bharadwaj. 4247-4274 [doi]
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• Cooperative Inverse Decision Theory for Uncertain PreferencesZachary Robertson, Hantao Zhang, Sanmi Koyejo. 5854-5868 [doi]
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• Heavy Sets with Applications to Interpretable Machine Learning DiagnosticsDmitry M. Malioutov, Sanjeeb Dash, Dennis Wei. 5918-5930 [doi]
• Stochastic Mirror Descent for Large-Scale Sparse RecoverySasila Ilandarideva, Yannis Bekri, Anatoli Iouditski, Vianney Perchet. 5931-5957 [doi]
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• Context-Specific Causal Discovery for Categorical Data Using Staged TreesManuele Leonelli, Gherardo Varando. 8871-8888 [doi]
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• Second Order Path Variationals in Non-Stationary Online LearningDheeraj Baby, Yu-Xiang Wang 0003. 9024-9075 [doi]
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• Domain Adaptation under Missingness ShiftHelen Zhou, Sivaraman Balakrishnan, Zachary C. Lipton. 9577-9606 [doi]
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• Theory and Algorithm for Batch Distribution Drift ProblemsPranjal Awasthi, Corinna Cortes, Christopher Mohri. 9826-9851 [doi]
• On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy EvaluationAnna Winnicki, R. Srikant 0001. 9852-9878 [doi]
• Precision/Recall on Imbalanced Test DataHongwei Shang, Jean-Marc Langlois, Kostas Tsioutsiouliklis, Changsung Kang. 9879-9891 [doi]
• Iterative Teaching by Data HallucinationZeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf. 9892-9913 [doi]
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• Probabilities of Causation: Role of Observational DataAng Li, Judea Pearl. 10012-10027 [doi]
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• Improving Adaptive Conformal Prediction Using Self-Supervised LearningNabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar. 10160-10177 [doi]
• Oracle-free Reinforcement Learning in Mean-Field Games along a Single Sample PathMuhammad Aneeq uz Zaman, Alec Koppel, Sujay Bhatt, Tamer Basar. 10178-10206 [doi]
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• Probabilistic Querying of Continuous-Time Event SequencesAlex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth. 10235-10251 [doi]
• Semantic Strengthening of Neuro-Symbolic LearningKareem Ahmed, Kai-Wei Chang, Guy Van den Broeck. 10252-10261 [doi]
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