Table of Contents

• Scalable Higher-Order Tensor Product Spline ModelsDavid Rügamer. 1-9 [doi]
• Fair k-center Clustering with OutliersDaichi Amagata. 10-18 [doi]
• A/B testing under Interference with Partial Network InformationShiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau. 19-27 [doi]
• Achieving Fairness through Separability: A Unified Framework for Fair Representation LearningTaeuk Jang, Hongchang Gao, Pengyi Shi, Xiaoqian Wang 0001. 28-36 [doi]
• Personalized Federated X-armed BanditWenjie Li, Qifan Song, Jean Honorio. 37-45 [doi]
• Non-Neighbors Also Matter to Kriging: A New Contrastive-Prototypical LearningZhishuai Li, Yunhao Nie, Ziyue Li 0002, Lei Bai 0001, Yisheng Lv, Rui Zhao 0001. 46-54 [doi]
• Boundary-Aware Uncertainty for Feature Attribution ExplainersDavin Hill, Aria Masoomi, Max Torop, Sandesh Ghimire, Jennifer G. Dy. 55-63 [doi]
• Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated OptimizationMathieu Even, Anastasia Koloskova, Laurent Massoulié. 64-72 [doi]
• Comparing Comparators in Generalization BoundsFredrik Hellström, Benjamin Guedj. 73-81 [doi]
• A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk MinimizationMathieu Dagréou, Thomas Moreau 0001, Samuel Vaiter, Pierre Ablin. 82-90 [doi]
• Better Batch for Deep Probabilistic Time Series ForecastingVincent Zhihao Zheng, Seongjin Choi, Lijun Sun. 91-99 [doi]
• Distributionally Robust Model-based Reinforcement Learning with Large State SpacesShyam Sundhar Ramesh, Pier Giuseppe Sessa, Yifan Hu, Andreas Krause 0001, Ilija Bogunovic. 100-108 [doi]
• Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with KernelsTamim El Ahmad, Luc Brogat-Motte, Pierre Laforgue, Florence d'Alché-Buc. 109-117 [doi]
• Ordinal Potential-based Player RatingNelson Vadori, Rahul Savani. 118-126 [doi]
• Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware PriorsTim G. J. Rudner, Ya Shi Zhang, Andrew Gordon Wilson, Julia Kempe. 127-135 [doi]
• Simple and scalable algorithms for cluster-aware precision medicineAmanda M. Buch, Conor Liston, Logan Grosenick. 136-144 [doi]
• A Specialized Semismooth Newton Method for Kernel-Based Optimal TransportTianyi Lin, Marco Cuturi, Michael I. Jordan. 145-153 [doi]
• Local Causal Discovery with Linear non-Gaussian Cyclic ModelsHaoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang 0001. 154-162 [doi]
• Density Uncertainty Layers for Reliable Uncertainty EstimationYookoon Park, David M. Blei. 163-171 [doi]
• Double InfoGAN for Contrastive AnalysisFlorence Carton, Robin Louiset, Pietro Gori. 172-180 [doi]
• Is this model reliable for everyone? Testing for strong calibrationJean Feng, Alexej Gossmann, Romain Pirracchio, Nicholas Petrick, Gene Pennello, Berkman Sahiner. 181-189 [doi]
• An Online Bootstrap for Time SeriesNicolai Palm, Thomas Nagler. 190-198 [doi]
• Better Representations via Adversarial Training in Pre-Training: A Theoretical PerspectiveYue Xing 0002, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng 0003. 199-207 [doi]
• Solving Attention Kernel Regression Problem via Pre-conditionerZhao Song 0002, Junze Yin, Lichen Zhang 0003. 208-216 [doi]
• Pixel-wise Smoothing for Certified Robustness against Camera Motion PerturbationsHanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao. 217-225 [doi]
• Identifying Copeland Winners in Dueling Bandits with IndifferencesViktor Bengs, Björn Haddenhorst, Eyke Hüllermeier. 226-234 [doi]
• Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?Kyurae Kim, Yian Ma, Jacob Gardner. 235-243 [doi]
• Fast Dynamic Sampling for Determinantal Point ProcessesZhao Song 0002, Junze Yin, Lichen Zhang 0003, Ruizhe Zhang 0001. 244-252 [doi]
• Best Arm Identification with Resource ConstraintsZitian Li, Wang Chi Cheung. 253-261 [doi]
• Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion ProcessesHaoming Yang, Ali-Hasan, Yuting Ng, Vahid Tarokh. 262-270 [doi]
• HintMiner: Automatic Question Hints Mining From Q&A Web Posts with Language Model via Self-Supervised LearningZhenyu Zhang, Jiudong Yang. 271-279 [doi]
• A Primal-Dual-Critic Algorithm for Offline Constrained Reinforcement LearningKihyuk Hong, Yuhang Li, Ambuj Tewari. 280-288 [doi]
• On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function ApproximationJiawei Huang, Batuhan Yardim, Niao He. 289-297 [doi]
• Breaking isometric ties and introducing priors in Gromov-Wasserstein distancesPinar Demetci, Quang-Huy Tran, Ievgen Redko, Ritambhara Singh. 298-306 [doi]
• Enhancing In-context Learning via Linear Probe CalibrationMomin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen. 307-315 [doi]
• DNNLasso: Scalable Graph Learning for Matrix-Variate DataMeixia Lin, Yangjing Zhang. 316-324 [doi]
• Fast 1-Wasserstein distance approximations using greedy strategiesGuillaume Houry, Han Bao 0002, Han Zhao 0002, Makoto Yamada. 325-333 [doi]
• Pure Exploration in Bandits with Linear ConstraintsEmil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi. 334-342 [doi]
• Emergent specialization from participation dynamics and multi-learner retrainingSarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel. 343-351 [doi]
• Optimal Sparse Survival TreesRui Zhang, Rui Xin, Margo I. Seltzer, Cynthia Rudin. 352-360 [doi]
• TenGAN: Pure Transformer Encoders Make an Efficient Discrete GAN for De Novo Molecular GenerationChen Li 0027, Yoshihiro Yamanishi. 361-369 [doi]
• Explanation-based Training with Differentiable Insertion/Deletion Metric-aware RegularizersYuya Yoshikawa, Tomoharu Iwata. 370-378 [doi]
• Multi-armed bandits with guaranteed revenue per armDorian Baudry, Nadav Merlis, Mathieu Benjamin Molina, Hugo Richard, Vianney Perchet. 379-387 [doi]
• Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited CommunicationHugo Richard, Etienne Boursier, Vianney Perchet. 388-396 [doi]
• Error bounds for any regression model using Gaussian processes with gradient informationRafael Savvides, Hoang Phuc Hau Luu, Kai Puolamäki. 397-405 [doi]
• Robust Non-linear Normalization of Heterogeneous Feature Distributions with Adaptive Tanh-EstimatorsFelip Guimerà Cuevas, Helmut Schmid. 406-414 [doi]
• Learning Granger Causality from Instance-wise Self-attentive Hawkes ProcessesDongxia Wu, Tsuyoshi Idé, Georgios Kollias, Jirí Navrátil 0001, Aurélie C. Lozano, Naoki Abe, Yian Ma, Rose Yu. 415-423 [doi]
• P-tensors: a General Framework for Higher Order Message Passing in Subgraph Neural NetworksAndrew R. Hands, Tianyi Sun, Risi Kondor. 424-432 [doi]
• Faster Convergence with MultiWay PreferencesAadirupa Saha, Vitaly Feldman, Yishay Mansour, Tomer Koren. 433-441 [doi]
• Testing Generated Distributions in GANs to Penalize Mode CollapseYanxiang Gong, Zhiwei Xie 0002, Mei Xie, Xin Ma 0004. 442-450 [doi]
• The Galerkin method beats Graph-Based Approaches for Spectral AlgorithmsVivien A Cabannnes, Francis Bach. 451-459 [doi]
• Online Distribution Learning with Local Privacy ConstraintsJin Sima, Changlong Wu, Olgica Milenkovic, Wojciech Szpankowski. 460-468 [doi]
• Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variableHyeok Kyu Kwon, Minwoo Chae. 469-477 [doi]
• Delegating Data Collection in Decentralized Machine LearningNivasini Ananthakrishnan, Stephen Bates, Michael I. Jordan, Nika Haghtalab. 478-486 [doi]
• Adaptive Compression in Federated Learning via Side InformationBerivan Isik, Francesco Pase, Deniz Gündüz, Sanmi Koyejo, Tsachy Weissman, Michele Zorzi. 487-495 [doi]
• Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics ApproachMasaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne. 496-504 [doi]
• Looping in the Human: Collaborative and Explainable Bayesian OptimizationMasaki Adachi, Brady Planden, David A. Howey, Michael A. Osborne, Sebastian Orbell, Natalia Ares, Krikamol Muandet, Siu Lun Chau. 505-513 [doi]
• Efficient Quantum Agnostic Improper Learning of Decision TreesSagnik Chatterjee, SAPV Tharrmashastha, Debajyoti Bera. 514-522 [doi]
• Meta Learning in Bandits within shared affine SubspacesSteven Bilaj, Sofien Dhouib, Setareh Maghsudi. 523-531 [doi]
• VEC-SBM: Optimal Community Detection with Vectorial Edges CovariatesGuillaume Braun, Masashi Sugiyama. 532-540 [doi]
• Robust Offline Reinforcement Learning with Heavy-Tailed RewardsJin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi. 541-549 [doi]
• The Risks of Recourse in Binary ClassificationHidde Fokkema, Damien Garreau, Tim van Erven. 550-558 [doi]
• Prior-dependent analysis of posterior sampling reinforcement learning with function approximationYingru Li, Zhi-Quan Luo. 559-567 [doi]
• Graph Partitioning with a Move BudgetMina Dalirrooyfard, Elaheh Fata, Majid Behbahani, Yuriy Nevmyvaka. 568-576 [doi]
• On Ranking-based Tests of IndependenceMyrto Limnios, Stéphan Clémençon. 577-585 [doi]
• Structured Transforms Across Spaces with Cost-Regularized Optimal TransportOthmane Sebbouh, Marco Cuturi, Gabriel Peyré. 586-594 [doi]
• Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection BiasAmbroise Odonnat, Vasilii Feofanov, Ievgen Redko. 595-603 [doi]
• Clustering Items From Adaptively Collected Inconsistent FeedbackShubham Gupta, Peter W. J. Staar, Christian de Sainte Marie. 604-612 [doi]
• Compression with Exact Error Distribution for Federated LearningMahmoud Hegazy, Rémi Leluc, Cheuk Ting Li, Aymeric Dieuleveut. 613-621 [doi]
• Deep anytime-valid hypothesis testingTeodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar. 622-630 [doi]
• Federated Linear Contextual Bandits with Heterogeneous ClientsEthan Blaser, Chuanhao Li, Hongning Wang. 631-639 [doi]
• LEDetection: A Simple Framework for Semi-Supervised Few-Shot Object DetectionPhi Vu Tran. 640-648 [doi]
• AsGrad: A Sharp Unified Analysis of Asynchronous-SGD AlgorithmsRustem Islamov, Mher Safaryan, Dan Alistarh. 649-657 [doi]
• Directional Optimism for Safe Linear BanditsSpencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh. 658-666 [doi]
• Theory-guided Message Passing Neural Network for Probabilistic InferenceZijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji. 667-675 [doi]
• Understanding Generalization of Federated Learning via Stability: Heterogeneity MattersZhenyu Sun, Xiaochun Niu, Ermin Wei. 676-684 [doi]
• Mechanics of Next Token Prediction with Self-AttentionYingcong Li, Yixiao Huang, Muhammed Emrullah Ildiz, Ankit Singh Rawat, Samet Oymak. 685-693 [doi]
• Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax OptimizationSiqi Zhang, Yifan Hu, Liang Zhang, Niao He. 694-702 [doi]
• TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional RegressionZelin He, Ying Sun, Runze Li. 703-711 [doi]
• Fusing Individualized Treatment Rules Using Secondary OutcomesDaiqi Gao, Yuanjia Wang, Donglin Zeng. 712-720 [doi]
• Exploration via linearly perturbed loss minimisationDavid Janz, Shuai Liu, Alex Ayoub, Csaba Szepesvári. 721-729 [doi]
• Proximal Causal Inference for Synthetic Control with SurrogatesJizhou Liu, Eric Tchetgen Tchetgen, Carlos Varjão. 730-738 [doi]
• Reparameterized Variational Rejection SamplingMartin Jankowiak, Du Phan. 739-747 [doi]
• E(3)-Equivariant Mesh Neural NetworksThuan Anh Trang, Nhat-Khang Ngo, Daniel T. Levy, Ngoc Thieu Vo, Siamak Ravanbakhsh, Truong-Son Hy. 748-756 [doi]
• A General Algorithm for Solving Rank-one Matrix SensingLianke Qin, Zhao Song 0002, Ruizhe Zhang 0001. 757-765 [doi]
• Oracle-Efficient Pessimism: Offline Policy Optimization In Contextual BanditsLequn Wang, Akshay Krishnamurthy, Alex Slivkins. 766-774 [doi]
• The Solution Path of SLOPEXavier Dupuis, Patrick Tardivel. 775-783 [doi]
• Lower-level Duality Based Reformulation and Majorization Minimization Algorithm for Hyperparameter OptimizationHe Chen, Haochen Xu, Rujun Jiang, Anthony Man-Cho So. 784-792 [doi]
• A Unified Framework for Discovering Discrete SymmetriesPavan Karjol, Rohan Kashyap, Aditya Gopalan, A. P. Prathosh. 793-801 [doi]
• Recovery Guarantees for Distributed-OMPChen Amiraz, Robert Krauthgamer, Boaz Nadler. 802-810 [doi]
• Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of OutliersMatteo Vilucchio, Emanuele Troiani, Vittorio Erba, Florent Krzakala. 811-819 [doi]
• Riemannian Laplace Approximation with the Fisher MetricHanlin Yu, Marcelo Hartmann, Bernardo Williams Moreno Sanchez, Mark Girolami, Arto Klami. 820-828 [doi]
• Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic SupportTim Reichelt, Luke Ong, Tom Rainforth. 829-837 [doi]
• Sharp error bounds for imbalanced classification: how many examples in the minority class?Anass Aghbalou, Anne Sabourin, François Portier. 838-846 [doi]
• Making Better Use of Unlabelled Data in Bayesian Active LearningFreddie Bickford Smith, Adam Foster 0001, Tom Rainforth. 847-855 [doi]
• Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization ProblemsNikita Puchkin, Eduard Gorbunov, Nikolay Kutuzov, Alexander V. Gasnikov. 856-864 [doi]
• Multi-Domain Causal Representation Learning via Weak Distributional InvariancesKartik Ahuja, Amin Mansouri, Yixin Wang. 865-873 [doi]
• Unsupervised Novelty Detection in Pretrained Representation Space with Locally Adapted Likelihood RatioAmirhossein Ahmadian, Yifan Ding, Gabriel Eilertsen, Fredrik Lindsten. 874-882 [doi]
• Adaptive Quasi-Newton and Anderson Acceleration Framework with Explicit Global (Accelerated) Convergence RatesDamien Scieur. 883-891 [doi]
• BOBA: Byzantine-Robust Federated Learning with Label SkewnessWenxuan Bao, Jun Wu, Jingrui He. 892-900 [doi]
• A White-Box False Positive Adversarial Attack Method on Contrastive Loss Based Offline Handwritten Signature Verification ModelsZhongliang Guo, Weiye Li, Yifei Qian, Ognjen Arandjelovic, Lei Fang. 901-909 [doi]
• Categorical Generative Model Evaluation via Synthetic Distribution CoarseningFlorence Regol, Mark Coates. 910-918 [doi]
• Monitoring machine learning-based risk prediction algorithms in the presence of performativityJean Feng, Alexej Gossmann, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio. 919-927 [doi]
• Learning-Based Algorithms for Graph Searching ProblemsAdela Frances DePavia, Erasmo Tani, Ali Vakilian. 928-936 [doi]
• Autoregressive BanditsFrancesco Bacchiocchi, Gianmarco Genalti, Davide Maran, Marco Mussi, Marcello Restelli, Nicola Gatti 0001, Alberto Maria Metelli. 937-945 [doi]
• DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging DataTaehyo Kim, Hai Shu, Qiran Jia, Mony de Leon. 946-954 [doi]
• Enhancing Hypergradients Estimation: A Study of Preconditioning and ReparameterizationZhenzhang Ye, Gabriel Peyré, Daniel Cremers, Pierre Ablin. 955-963 [doi]
• MINTY: Rule-based models that minimize the need for imputing features with missing valuesLena Stempfle, Fredrik D. Johansson. 964-972 [doi]
• Multi-Dimensional Hyena for Spatial Inductive BiasItamar Zimerman, Lior Wolf. 973-981 [doi]
• Graph Machine Learning through the Lens of Bilevel OptimizationAmber Yijia Zheng, Tong He 0002, Yixuan Qiu, Minjie Wang, David Wipf. 982-990 [doi]
• Robust Sparse VotingYoussef Allouah, Rachid Guerraoui, Lê Nguyên Hoang, Oscar Villemaud. 991-999 [doi]
• Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over QuantitySiddharth Joshi, Arnav Jain, Ali Payani, Baharan Mirzasoleiman. 1000-1008 [doi]
• Efficient Low-Dimensional Compression of Overparameterized ModelsSoo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, Qing Qu 0001. 1009-1017 [doi]
• Data-Adaptive Probabilistic Likelihood Approximation for Ordinary Differential EquationsMohan Wu, Martin Lysy. 1018-1026 [doi]
• Fairness in Submodular Maximization over a Matroid ConstraintMarwa El Halabi, Jakub Tarnawski, Ashkan Norouzi-Fard, Thuy Duong Vuong. 1027-1035 [doi]
• Unified Transfer Learning in High-Dimensional Linear RegressionShuo Shuo Liu. 1036-1044 [doi]
• Hidden yet quantifiable: A lower bound for confounding strength using randomized trialsPiersilvio De Bartolomeis, Javier Abad Martinez, Konstantin Donhauser, Fanny Yang. 1045-1053 [doi]
• Towards Achieving Sub-linear Regret and Hard Constraint Violation in Model-free RLArnob Ghosh, Xingyu Zhou 0001, Ness B. Shroff. 1054-1062 [doi]
• Distributionally Robust Quickest Change Detection using Wasserstein Uncertainty SetsLiyan Xie, Yuchen Liang, Venugopal V. Veeravalli. 1063-1071 [doi]
• Quantifying Uncertainty in Natural Language Explanations of Large Language ModelsSree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju. 1072-1080 [doi]
• Submodular Minimax Optimization: Finding Effective SetsLoay Raed Mualem, Ethan R. Elenberg, Moran Feldman, Amin Karbasi. 1081-1089 [doi]
• Effect of Ambient-Intrinsic Dimension Gap on Adversarial VulnerabilityRajdeep Haldar, Yue Xing 0002, Qifan Song. 1090-1098 [doi]
• Information-theoretic Analysis of Bayesian Test Data SensitivityFutoshi Futami, Tomoharu Iwata. 1099-1107 [doi]
• Scalable Algorithms for Individual Preference Stable ClusteringRon Mosenzon, Ali Vakilian. 1108-1116 [doi]
• Orthogonal Gradient Boosting for Simpler Additive Rule EnsemblesFan Yang, Pierre Le Bodic, Michael Kamp, Mario Boley. 1117-1125 [doi]
• When No-Rejection Learning is Consistent for Regression with RejectionXiaocheng Li, Shang Liu, Chunlin Sun, Hanzhao Wang. 1126-1134 [doi]
• Filter, Rank, and Prune: Learning Linear Cyclic Gaussian Graphical ModelsSoheun Yi, Sanghack Lee. 1135-1143 [doi]
• Robust variance-regularized risk minimization with concomitant scalingMatthew J. Holland. 1144-1152 [doi]
• Fast and Adversarial Robust Kernelized SDU LearningYajing Fan, Wanli Shi, Yi Chang, Bin Gu 0001. 1153-1161 [doi]
• Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order OptimizationZhou Zhai, Wanli Shi, Heng Huang, Yi Chang, Bin Gu 0001. 1162-1170 [doi]
• Efficient Graph Laplacian Estimation by Proximal NewtonYakov Medvedovsky, Eran Treister, Tirza S. Routtenberg. 1171-1179 [doi]
• Adaptive Experiment Design with Synthetic ControlsAlihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar. 1180-1188 [doi]
• Online non-parametric likelihood-ratio estimation by Pearson-divergence functional minimizationAlejandro D. de la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos. 1189-1197 [doi]
• Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness ResultsAinhize Barrainkua, Paula Gordaliza, Jose A. Lozano, Novi Quadrianto. 1198-1206 [doi]
• Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved RatesAhmad Rammal, Kaja Gruntkowska, Nikita Fedin, Eduard Gorbunov, Peter Richtárik. 1207-1215 [doi]
• Best-of-Both-Worlds Algorithms for Linear Contextual BanditsYuko Kuroki, Alberto Rumi, Taira Tsuchiya, Fabio Vitale, Nicolò Cesa-Bianchi. 1216-1224 [doi]
• Fixed-Budget Real-Valued Combinatorial Pure Exploration of Multi-Armed BanditShintaro Nakamura, Masashi Sugiyama. 1225-1233 [doi]
• Scalable Learning of Item Response Theory ModelsSusanne Frick, Amer Krivosija, Alexander Munteanu. 1234-1242 [doi]
• Corruption-Robust Offline Two-Player Zero-Sum Markov GamesAndi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic. 1243-1251 [doi]
• Risk Seeking Bayesian Optimization under Uncertainty for Obtaining ExtremumShogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Yu Inatsu. 1252-1260 [doi]
• Quantized Fourier and Polynomial Features for more Expressive Tensor Network ModelsFrederiek Wesel, Kim Batselier. 1261-1269 [doi]
• Fair Soft ClusteringRune D. Kjærsgaard, Pekka Parviainen, Saket Saurabh 0001, Madhumita Kundu, Line H. Clemmensen. 1270-1278 [doi]
• Simulation-Free Schrödinger Bridges via Score and Flow MatchingAlexander Tong 0001, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio. 1279-1287 [doi]
• Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted TreesAlexia Jolicoeur-Martineau, Kilian Fatras, Tal Kachman. 1288-1296 [doi]
• Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernelsRaphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber. 1297-1305 [doi]
• Intrinsic Gaussian Vector Fields on ManifoldsDaniel Robert-Nicoud, Andreas Krause 0001, Viacheslav Borovitskiy. 1306-1314 [doi]
• A Unifying Variational Framework for Gaussian Process Motion PlanningLucas Cosier, Rares Iordan, Sicelukwanda N. T. Zwane, Giovanni Franzese, James T. Wilson, Marc Peter Deisenroth, Alexander Terenin, Yasemin Bekiroglu. 1315-1323 [doi]
• MMD-based Variable Importance for Distributional Random ForestClément Bénard, Jeffrey Näf, Julie Josse. 1324-1332 [doi]
• Efficiently Computable Safety Bounds for Gaussian Processes in Active LearningJörn Tebbe, Christoph Zimmer, Ansgar Steland, Markus Lange-Hegermann, Fabian Mies. 1333-1341 [doi]
• Federated Learning For Heterogeneous Electronic Health Records Utilising Augmented Temporal Graph Attention NetworksSoheila Molaei, Anshul Thakur, Ghazaleh Niknam, Andrew A. S. Soltan, Hadi Zare 0001, David A. Clifton. 1342-1350 [doi]
• Adaptive Discretization for Event PredicTion (ADEPT)Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael J. Pencina, Matthew Engelhard. 1351-1359 [doi]
• Generalization Bounds for Label Noise Stochastic Gradient DescentJung Eun Huh, Patrick Rebeschini. 1360-1368 [doi]
• Adaptive Parametric Prototype Learning for Cross-Domain Few-Shot ClassificationMarzi Heidari, Abdullah Alchihabi, Qing En, Yuhong Guo. 1369-1377 [doi]
• Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction FunctionsZulqarnain Khan, Davin Hill, Aria Masoomi, Joshua T. Bone, Jennifer G. Dy. 1378-1386 [doi]
• Importance Matching Lemma for Lossy Compression with Side InformationBuu Phan, Ashish Khisti, Christos Louizos. 1387-1395 [doi]
• Certified private data release for sparse Lipschitz functionsKonstantin Donhauser, Johan Lokna, Amartya Sanyal, March Boedihardjo, Robert Hönig, Fanny Yang. 1396-1404 [doi]
• Sequence Length Independent Norm-Based Generalization Bounds for TransformersJacob Trauger, Ambuj Tewari. 1405-1413 [doi]
• Subsampling Error in Stochastic Gradient Langevin DiffusionsKexin Jin, ChenGuang Liu, Jonas Latz. 1414-1422 [doi]
• Analysis of Privacy Leakage in Federated Large Language ModelsMinh N. Vu, Truc D. T. Nguyen, Tre' R. Jeter, My T. Thai. 1423-1431 [doi]
• Exploring the Power of Graph Neural Networks in Solving Linear Optimization ProblemsChendi Qian, Didier Chételat, Christopher Morris 0001. 1432-1440 [doi]
• Cross-model Mutual Learning for Exemplar-based Medical Image SegmentationQing En, Yuhong Guo. 1441-1449 [doi]
• Online Calibrated and Conformal Prediction Improves Bayesian OptimizationShachi Deshpande, Charles Marx, Volodymyr Kuleshov. 1450-1458 [doi]
• Offline Policy Evaluation and Optimization Under ConfoundingChinmaya Kausik, Yangyi Lu, Kevin Tan, Maggie Makar, Yixin Wang, Ambuj Tewari. 1459-1467 [doi]
• Confident Feature RankingBitya Neuhof, Yuval Benjamini. 1468-1476 [doi]
• Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and ApplicationsJie Hu, Vishwaraj Doshi, Do Young Eun. 1477-1485 [doi]
• Taming False Positives in Out-of-Distribution Detection with Human FeedbackHarit Vishwakarma, Heguang Lin, Ramya Korlakai Vinayak. 1486-1494 [doi]
• On the Privacy of Selection Mechanisms with Gaussian NoiseJonathan Lebensold, Doina Precup, Borja Balle. 1495-1503 [doi]
• Transductive conformal inference with adaptive scoresUlysse Gazin, Gilles Blanchard, Étienne Roquain. 1504-1512 [doi]
• Learning Latent Partial Matchings with Gumbel-IPF NetworksHedda Cohen Indelman, Tamir Hazan. 1513-1521 [doi]
• On Counterfactual Metrics for Social Welfare: Incentives, Ranking, and Information AsymmetrySerena Lutong Wang, Stephen Bates, P. M. Aronow, Michael I. Jordan. 1522-1530 [doi]
• Data-Driven Online Model Selection With Regret GuaranteesChristoph Dann, Claudio Gentile, Aldo Pacchiano. 1531-1539 [doi]
• Integrating Uncertainty Awareness into Conformalized Quantile RegressionRaphael Rossellini, Rina Foygel Barber, Rebecca Willett. 1540-1548 [doi]
• On the Expected Size of Conformal Prediction SetsGuneet S. Dhillon, George Deligiannidis, Tom Rainforth. 1549-1557 [doi]
• Estimation of partially known Gaussian graphical models with score-based structural priorsMartin Sevilla, Antonio G. Marques, Santiago Segarra. 1558-1566 [doi]
• Model-Based Best Arm Identification for Decreasing BanditsSho Takemori, Yuhei Umeda, Aditya Gopalan. 1567-1575 [doi]
• Thompson Sampling Itself is Differentially PrivateTingting Ou, Rachel Cummings, Marco Avella. 1576-1584 [doi]
• A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarityZhihan Xiong, Romain Camilleri, Maryam Fazel, Lalit Jain, Kevin G. Jamieson. 1585-1593 [doi]
• Fair Supervised Learning with A Simple Random Sampler of Sensitive AttributesJinwon Sohn, Qifan Song, Guang Lin. 1594-1602 [doi]
• Absence of spurious solutions far from ground truth: A low-rank analysis with high-order lossesZiye Ma, Ying Chen, Javad Lavaei, Somayeh Sojoudi. 1603-1611 [doi]
• FedFisher: Leveraging Fisher Information for One-Shot Federated LearningDivyansh Jhunjhunwala, Shiqiang Wang 0001, Gauri Joshi. 1612-1620 [doi]
• Causal Discovery under Off-Target InterventionsDavin Choo, Kirankumar Shiragur, Caroline Uhler. 1621-1629 [doi]
• Feasible Q-Learning for Average Reward Reinforcement LearningYing Jin, Ramki Gummadi, Zhengyuan Zhou, Jose H. Blanchet. 1630-1638 [doi]
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• Adaptivity of Diffusion Models to Manifold StructuresRong Tang, Yun Yang. 1648-1656 [doi]
• Conformalized Deep Splines for Optimal and Efficient Prediction SetsNathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani, Gabriele Scalia. 1657-1665 [doi]
• Accuracy-Preserving Calibration via Statistical Modeling on Probability SimplexYasushi Esaki, Akihiro Nakamura, Keisuke Kawano, Ryoko Tokuhisa, Takuro Kutsuna. 1666-1674 [doi]
• Smoothness-Adaptive Dynamic Pricing with Nonparametric Demand LearningZeqi Ye, Hansheng Jiang. 1675-1683 [doi]
• Optimal Exploration is no harder than Thompson SamplingZhaoqi Li, Kevin G. Jamieson, Lalit Jain. 1684-1692 [doi]
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• Robust Data Clustering with Outliers via Transformed Tensor Low-Rank RepresentationTong Wu. 1756-1764 [doi]
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• An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax OptimizationLesi Chen, Haishan Ye, Luo Luo. 1990-1998 [doi]
• Vector Quantile Regression on ManifoldsMarco Pegoraro 0002, Sanketh Vedula, Aviv Rosenberg 0001, Irene Tallini, Emanuele Rodolà, Alex M. Bronstein. 1999-2007 [doi]
• Near-Optimal Convex Simple Bilevel Optimization with a Bisection MethodJiulin Wang, Xu Shi, Rujun Jiang. 2008-2016 [doi]
• Tackling the XAI Disagreement Problem with Regional ExplanationsGabriel Laberge, Yann Batiste Pequignot, Mario Marchand, Foutse Khomh. 2017-2025 [doi]
• Training Implicit Generative Models via an Invariant Statistical LossJosé Manuel de Frutos, Pablo M. Olmos, Manuel Alberto Vazquez Lopez, Joaquín Míguez. 2026-2034 [doi]
• RL in Markov Games with Independent Function Approximation: Improved Sample Complexity Bound under the Local Access ModelJunyi Fan, Yuxuan Han, Jialin Zeng, Jian-Feng Cai 0001, Yang Wang, Yang Xiang, Jiheng Zhang. 2035-2043 [doi]
• Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential GamesJing Dong 0008, Baoxiang Wang 0001, Yaoliang Yu. 2044-2052 [doi]
• GmGM: a fast multi-axis Gaussian graphical modelEthan B. Andrew, David Westhead, Luisa Cutillo. 2053-2061 [doi]
• On Convergence in Wasserstein Distance and f-divergence Minimization ProblemsCheuk Ting Li, Jingwei Zhang, Farzan Farnia. 2062-2070 [doi]
• Sparse and Faithful Explanations Without Sparse ModelsYiyang Sun, Zhi Chen 0009, Vittorio Orlandi, Tong Wang 0011, Cynthia Rudin. 2071-2079 [doi]
• Extragradient Type Methods for Riemannian Variational Inequality ProblemsZihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao. 2080-2088 [doi]
• Learning Sparse Codes with Entropy-Based ELBOsDmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke. 2089-2097 [doi]
• Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed ResponsesShiliang Zuo. 2098-2106 [doi]
• Robust Approximate Sampling via Stochastic Gradient Barker DynamicsLorenzo Mauri, Giacomo Zanella. 2107-2115 [doi]
• Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient ViewpointHaoyue Tang, Tian Xie, Aosong Feng, Hanyu Wang, Chenyang Zhang, Yang Bai. 2116-2124 [doi]
• Enhancing Distributional Stability among Sub-populationsJiashuo Liu, Jiayun Wu, Jie Peng, Xiaoyu Wu, Yang Zheng, Bo Li 0064, Peng Cui 0001. 2125-2133 [doi]
• Safe and Interpretable Estimation of Optimal Treatment RegimesHarsh Parikh, Quinn Lanners, Zade Akras, Sahar Zafar, M. Brandon Westover, Cynthia Rudin, Alexander Volfovsky. 2134-2142 [doi]
• Probabilistic Integral CircuitsGennaro Gala, Cassio P. de Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur. 2143-2151 [doi]
• Learning Extensive-Form Perfect Equilibria in Two-Player Zero-Sum Sequential GamesMartino Bernasconi, Alberto Marchesi 0001, Francesco Trovò. 2152-2160 [doi]
• Understanding Progressive Training Through the Framework of Randomized Coordinate DescentRafal Szlendak, Elnur Gasanov, Peter Richtárik. 2161-2169 [doi]
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• On the Theoretical Expressive Power and the Design Space of Higher-Order Graph TransformersCai Zhou, Rose Yu, Yusu Wang 0001. 2179-2187 [doi]
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• Free-form Flows: Make Any Architecture a Normalizing FlowFelix Draxler, Peter Sorrenson, Lea Zimmermann, Armand Rousselot, Ullrich Köthe. 2197-2205 [doi]
• Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror DescentBianca Marin Moreno, Margaux Brégère, Pierre Gaillard, Nadia Oudjane. 2206-2214 [doi]
• Online learning in bandits with predicted contextYongyi Guo, Ziping Xu, Susan A. Murphy. 2215-2223 [doi]
• Optimising Distributions with Natural Gradient SurrogatesJonathan So, Richard E. Turner. 2224-2232 [doi]
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• Sum-max Submodular BanditsStephen U. Pasteris, Alberto Rumi, Fabio Vitale, Nicolò Cesa-Bianchi. 2323-2331 [doi]
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• Achieving Group Distributional Robustness and Minimax Group Fairness with Interpolating ClassifiersNatalia Martínez, Martín Bertrán, Guillermo Sapiro. 2629-2637 [doi]
• Graph fission and cross-validationJames Leiner, Aaditya Ramdas. 2638-2646 [doi]
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• Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexityVincent Souveton, Arnaud Guillin, Jens Jasche, Guilhem Lavaux, Manon Michel. 3178-3186 [doi]
• Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous DataYuqin Yang, Saber Salehkaleybar, Negar Kiyavash. 3187-3195 [doi]
• XB-MAML: Learning Expandable Basis Parameters for Effective Meta-Learning with Wide Task CoverageJae Jun Lee, Sung Whan Yoon. 3196-3204 [doi]
• General Tail Bounds for Non-Smooth Stochastic Mirror DescentKhaled Eldowa, Andrea Paudice. 3205-3213 [doi]
• Symmetric Equilibrium Learning of VAEsBoris Flach, Dmitrij Schlesinger, Alexander Shekhovtsov. 3214-3222 [doi]
• On Feynman-Kac training of partial Bayesian neural networksZheng Zhao 0004, Sebastian Mair 0001, Thomas B. Schön, Jens Sjölund. 3223-3231 [doi]
• No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity ConstraintsArpan Losalka, Jonathan Scarlett. 3232-3240 [doi]
• Learning multivariate temporal point processes via the time-change theoremGuilherme Augusto Zagatti, See-Kiong Ng, Stéphane Bressan. 3241-3249 [doi]
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• SDMTR: A Brain-inspired Transformer for Relation InferenceXiangyu Zeng, Jie Lin, Piao Hu, Zhihao Li, Tianxi Huang. 3259-3267 [doi]
• Directed Hypergraph Representation Learning for Link PredictionZitong Ma, Wenbo Zhao, Zhe Yang. 3268-3276 [doi]
• Formal Verification of Unknown Stochastic Systems via Non-parametric EstimationZhi Zhang, Chenyu Ma, Saleh Soudijani, Sadegh Soudjani. 3277-3285 [doi]
• Variational ResamplingOskar Kviman, Nicola Branchini, Víctor Elvira, Jens Lagergren. 3286-3294 [doi]
• Implicit Bias in Noisy-SGD: With Applications to Differentially Private TrainingTom Sander, Maxime Sylvestre, Alain Durmus. 3295-3303 [doi]
• Training a Tucker Model With Shared Factors: a Riemannian Optimization ApproachIvan Peshekhonov, Aleksey Arzhantsev, Maxim V. Rakhuba. 3304-3312 [doi]
• Don't Be Pessimistic Too Early: Look K Steps Ahead!Chaoqi Wang, Ziyu Ye, Kevin Murphy, Yuxin Chen 0001. 3313-3321 [doi]
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• Identifiable Feature Learning for Spatial Data with Nonlinear ICAHermanni Hälvä, Jonathan So, Richard E. Turner, Aapo Hyvärinen. 3331-3339 [doi]
• Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional DataSrikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky. 3340-3348 [doi]
• Score Operator Newton transportNisha Chandramoorthy, Florian T. Schaefer, Youssef M. Marzouk. 3349-3357 [doi]
• ALAS: Active Learning for Autoconversion Rates Prediction from Satellite DataMaria C. Novitasari, Johannes Quaas, Miguel Rodrigues. 3358-3366 [doi]
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• Posterior Uncertainty Quantification in Neural Networks using Data AugmentationLuhuan Wu, Sinead A. Williamson. 3376-3384 [doi]
• DHMConv: Directed Hypergraph Momentum Convolution FrameworkWenbo Zhao, Zitong Ma, Zhe Yang. 3385-3393 [doi]
• From Data Imputation to Data Cleaning - Automated Cleaning of Tabular Data Improves Downstream Predictive PerformanceSebastian Jäger, Felix Biessmann. 3394-3402 [doi]
• Discriminator Guidance for Autoregressive Diffusion ModelsFilip Ekström Kelvinius, Fredrik Lindsten. 3403-3411 [doi]
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• On-Demand Federated Learning for Arbitrary Target Class DistributionsIsu Jeong, Seulki Lee. 3421-3429 [doi]
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• Data-Driven Confidence Intervals with Optimal Rates for the Mean of Heavy-Tailed DistributionsAmbrus Tamás, Szabolcs Szentpéteri, Balázs Csanád Csáji. 3439-3447 [doi]
• Communication-Efficient Federated Learning With Data and Client HeterogeneityHossein Zakerinia, Shayan Talaei, Giorgi Nadiradze, Dan Alistarh. 3448-3456 [doi]
• SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated OptimizationYann Fraboni, Martin Van Waerebeke, Kevin Scaman, Richard Vidal, Laetitia Kameni, Marco Lorenzi. 3457-3465 [doi]
• Consistent and Asymptotically Unbiased Estimation of Proper Calibration ErrorsTeodora Popordanoska, Sebastian Gregor Gruber, Aleksei Tiulpin, Florian Büttner, Matthew B. Blaschko. 3466-3474 [doi]
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• Trigonometric Quadrature Fourier Features for Scalable Gaussian Process RegressionKevin Li, Max Balakirsky, Simon Mak. 3484-3492 [doi]
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• SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through StratificationPatrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier. 3520-3528 [doi]
• Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects EstimationVinod Kumar Chauhan, Jiandong Zhou, Ghadeer O. Ghosheh, Soheila Molaei, David A. Clifton. 3529-3537 [doi]
• Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance BoundsAlexandra Maria Hotti, Lennart Alexander Van der Goten, Jens Lagergren. 3538-3546 [doi]
• Length independent PAC-Bayes bounds for Simple RNNsVolodimir Mitarchuk, Clara Lacroce, Rémi Eyraud, Rémi Emonet, Amaury Habrard, Guillaume Rabusseau. 3547-3555 [doi]
• Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear NetworksHristo Papazov, Scott Pesme, Nicolas Flammarion. 3556-3564 [doi]
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• Identification and Estimation of "Causes of Effects" using Covariate-Mediator InformationRyusei Shingaki, Manabu Kuroki. 3574-3582 [doi]
• Sequential learning of the Pareto front for multi-objective banditsÉlise Crepon, Aurélien Garivier, Wouter M. Koolen. 3583-3591 [doi]
• Equivalence Testing: The Power of Bounded AdaptivityDiptarka Chakraborty, Sourav Chakraborty 0001, Gunjan Kumar, Kuldeep S. Meel. 3592-3600 [doi]
• Shape Arithmetic Expressions: Advancing Scientific Discovery Beyond Closed-Form EquationsKrzysztof Kacprzyk, Mihaela van der Schaar. 3601-3609 [doi]
• On the estimation of persistence intensity functions and linear representations of persistence diagramsWeichen Wu, Jisu Kim, Alessandro Rinaldo. 3610-3618 [doi]
• Optimal estimation of Gaussian (poly)treesYuhao Wang, Ming Gao, Wai Ming Tai, Bryon Aragam, Arnab Bhattacharyya 0001. 3619-3627 [doi]
• Approximate Bayesian Class-Conditional Models under Continuous Representation ShiftThomas L. Lee, Amos J. Storkey. 3628-3636 [doi]
• Dissimilarity BanditsPaolo Battellani, Alberto Maria Metelli, Francesco Trovò. 3637-3645 [doi]
• Consistent Optimal Transport with Empirical Conditional MeasuresPiyushi Manupriya, Rachit Keerti Das, Sayantan Biswas, Sakethanath Nath Jagarlapudi. 3646-3654 [doi]
• On the Impact of Overparameterization on the Training of a Shallow Neural Network in High DimensionsSimon Martin 0006, Francis Bach, Giulio Biroli. 3655-3663 [doi]
• Mixed Models with Multiple Instance LearningJan P. Engelmann, Alessandro Palma, Jakub M. Tomczak, Fabian J. Theis, Francesco Paolo Casale. 3664-3672 [doi]
• Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function ApproximationJiayi Huang, Han Zhong 0001, Liwei Wang, Lin Yang 0011. 3673-3681 [doi]
• Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational InequalitiesKonstantinos Emmanouilidis, René Vidal, Nicolas Loizou. 3682-3690 [doi]
• Inconsistency of Cross-Validation for Structure Learning in Gaussian Graphical ModelsZhao Lyu, Wai Ming Tai, Mladen Kolar, Bryon Aragam. 3691-3699 [doi]
• Differentially Private Conditional Independence TestingIden Kalemaj, Shiva Prasad Kasiviswanathan, Aaditya Ramdas. 3700-3708 [doi]
• Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent OraclesKevin Scaman, Mathieu Even, Batiste Le Bars, Laurent Massoulié. 3709-3717 [doi]
• On the Nyström Approximation for Preconditioning in Kernel MachinesAmirhesam Abedsoltan, Parthe Pandit, Luis Rademacher, Mikhail Belkin. 3718-3726 [doi]
• Learning to Rank for Optimal Treatment Allocation Under Resource ConstraintsFahad Kamran, Maggie Makar, Jenna Wiens. 3727-3735 [doi]
• Fair Machine Unlearning: Data Removal while Mitigating DisparitiesAlex Oesterling, Jiaqi Ma, Flávio P. Calmon, Himabindu Lakkaraju. 3736-3744 [doi]
• On the Effect of Key Factors in Spurious Correlation: A theoretical PerspectiveYipei Wang, Xiaoqian Wang 0001. 3745-3753 [doi]
• Hodge-Compositional Edge Gaussian ProcessesMaosheng Yang, Viacheslav Borovitskiy, Elvin Isufi. 3754-3762 [doi]
• Manifold-Aligned Counterfactual Explanations for Neural NetworksAsterios Tsiourvas, Wei Sun 0031, Georgia Perakis. 3763-3771 [doi]
• Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient DescentJialun Zhang, Richard Y. Zhang, Hong Ming Chiu. 3772-3780 [doi]
• LP-based Construction of DC Decompositions for Efficient Inference of Markov Random FieldsChaitanya Murti, Dhruva Kashyap, Chiranjib Bhattacharyya. 3781-3789 [doi]
• On the Misspecification of Linear Assumptions in Synthetic ControlsAchille O. R. Nazaret, Claudia Shi, David M. Blei. 3790-3798 [doi]
• The sample complexity of ERMs in stochastic convex optimizationDaniel Carmon, Amir Yehudayoff, Roi Livni. 3799-3807 [doi]
• Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine LearningAmey P. Pasarkar, Adji Bousso Dieng. 3808-3816 [doi]
• On cyclical MCMC samplingLiwei Wang, Xinru Liu, Aaron Smith, Aguemon Y. Atchadé. 3817-3825 [doi]
• FairRR: Pre-Processing for Group Fairness through Randomized ResponseJoshua John Ward, Xianli Zeng, Guang Cheng. 3826-3834 [doi]
• Fitting ARMA Time Series Models without Identification: A Proximal ApproachYin Liu, Sam Davanloo Tajbakhsh. 3835-3843 [doi]
• Unsupervised Change Point Detection in Multivariate Time SeriesDaoping Wu, Suhas Gundimeda, Shaoshuai Mou, Christopher J. Quinn. 3844-3852 [doi]
• Proving Linear Mode Connectivity of Neural Networks via Optimal TransportDamien Ferbach, Baptiste Goujaud, Gauthier Gidel, Aymeric Dieuleveut. 3853-3861 [doi]
• Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient FlowYinuo Ren, Tesi Xiao, Tanmay Gangwani, Anshuka Rangi, Holakou Rahmanian, Lexing Ying, Subhajit Sanyal. 3862-3870 [doi]
• Adaptive importance sampling for heavy-tailed distributions via α-divergence minimizationThomas Guilmeau, Nicola Branchini, Émilie Chouzenoux, Victor Elvira. 3871-3879 [doi]
• A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary OpponentMehdi Jafarnia-Jahromi, Rahul A. Jain, Ashutosh Nayyar. 3880-3888 [doi]
• Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov GamesYang Cai 0001, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng. 3889-3897 [doi]
• Multi-Agent Bandit Learning through Heterogeneous Action Erasure ChannelsOsama A. Hanna, Merve Karakas, Lin Yang 0011, Christina Fragouli. 3898-3906 [doi]
• Efficient Variational Sequential Information ControlJianwei Shen, Jason Pacheco. 3907-3915 [doi]
• Conditions on Preference Relations that Guarantee the Existence of Optimal PoliciesJonathan Colaço Carr, Prakash Panangaden, Doina Precup. 3916-3924 [doi]
• Membership Testing in Markov Equivalence Classes via Independence QueriesJiaqi Zhang, Kirankumar Shiragur, Caroline Uhler. 3925-3933 [doi]
• Functional Flow MatchingGavin Kerrigan, Giosue Migliorini, Padhraic Smyth. 3934-3942 [doi]
• Learning Under Random Distributional ShiftsKirk C. Bansak, Elisabeth Paulson, Dominik Rothenhäusler. 3943-3951 [doi]
• Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural NetworksKaiting Liu, Zahra Atashgahi, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu. 3952-3960 [doi]
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• Anytime-Constrained Reinforcement LearningJeremy McMahan, Xiaojin Zhu 0001. 4321-4329 [doi]
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• Soft-constrained Schrödinger Bridge: a Stochastic Control ApproachJhanvi Garg, Xianyang Zhang, Quan Zhou. 4429-4437 [doi]
• Coreset Markov chain Monte CarloNaitong Chen, Trevor Campbell. 4438-4446 [doi]
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• Improving Robustness via Tilted Exponential Layer: A Communication-Theoretic PerspectiveBhagyashree Puranik, Ahmad Beirami, Yao Qin 0001, Upamanyu Madhow. 4510-4518 [doi]
• On the Generalization Ability of Unsupervised PretrainingYuyang Deng, Junyuan Hong, Jiayu Zhou, Mehrdad Mahdavi. 4519-4527 [doi]
• Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural NetworksWaleed Mustafa, Philipp Liznerski, Antoine Ledent, Dennis Wagner, Puyu Wang, Marius Kloft. 4528-4536 [doi]
• BLIS-Net: Classifying and Analyzing Signals on GraphsCharles Xu 0004, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter. 4537-4545 [doi]
• Think Before You Duel: Understanding Complexities of Preference Learning under Constrained ResourcesRohan Deb, Aadirupa Saha, Arindam Banerjee. 4546-4554 [doi]
• Fast Fourier Bayesian QuadratureHouston Warren, Fabio Ramos 0001. 4555-4563 [doi]
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• To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared ModelsCyrus Cousins, I. Elizabeth Kumar, Suresh Venkatasubramanian. 4573-4581 [doi]
• Two Birds with One Stone: Enhancing Uncertainty Quantification and Interpretability with Graph Functional Neural ProcessLingkai Kong, Haotian Sun, Yuchen Zhuang, Haorui Wang, Wenhao Mu, Chao Zhang. 4582-4590 [doi]
• Sample Efficient Learning of Factored Embeddings of Tensor FieldsTaemin Heo, Chandrajit Bajaj. 4591-4599 [doi]
• autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithmMiguel Biron-Lattes, Nikola Surjanovic, Saifuddin Syed, Trevor Campbell, Alexandre Bouchard-Côté. 4600-4608 [doi]
• Causal Bandits with General Causal Models and InterventionsZirui Yan, Dennis Wei, Dmitriy A. Katz, Prasanna Sattigeri, Ali Tajer. 4609-4617 [doi]
• Surrogate Active Subspaces for Jump-Discontinuous FunctionsNathan Wycoff. 4618-4626 [doi]
• Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and ConstraintsAhmet Alacaoglu, Stephen J. Wright 0001. 4627-4635 [doi]
• Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic GraphsMishfad Shaikh Veedu, Deepjyoti Deka, Murti V. Salapaka. 4636-4644 [doi]
• Pathwise Explanation of ReLU Neural NetworksSeongwoo Lim, Won Jo, Joohyung Lee, Jaesik Choi. 4645-4653 [doi]
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• Mixture-of-Linear-Experts for Long-term Time Series ForecastingRonghao Ni, Zinan Lin 0001, Shuaiqi Wang, Giulia Fanti. 4672-4680 [doi]
• On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: a regret lower bound for WSU-UXAli Mortazavi, Junhao Lin, Nishant A. Mehta. 4681-4689 [doi]
• Faster Recalibration of an Online Predictor via ApproachabilityPrincewill Okoroafor, Robert D. Kleinberg, Wen Sun. 4690-4698 [doi]
• Provable Policy Gradient Methods for Average-Reward Markov Potential GamesMin Cheng, Ruida Zhou, P. R. Kumar 0001, Chao Tian 0002. 4699-4707 [doi]
• A Cubic-regularized Policy Newton Algorithm for Reinforcement LearningMizhaan Prajit Maniyar, Prashanth L. A., Akash Mondal, Shalabh Bhatnagar. 4708-4716 [doi]
• Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes ApproachJuanwu Lu, Wei Zhan, Masayoshi Tomizuka, Yeping Hu. 4717-4725 [doi]
• Understanding Inverse Scaling and Emergence in Multitask Representation LearningMuhammed Emrullah Ildiz, Zhe Zhao, Samet Oymak. 4726-4734 [doi]
• Sharpened Lazy Incremental Quasi-Newton MethodAakash Sunil Lahoti, Spandan Senapati, Ketan Rajawat, Alec Koppel. 4735-4743 [doi]
• Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization ApproachYinan Li, Chicheng Zhang. 4744-4752 [doi]
• Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class AbstentionAnqi Mao, Mehryar Mohri, Yutao Zhong 0002. 4753-4761 [doi]
• Deep Classifier Mimicry without Data AccessSteven Braun, Martin Mundt, Kristian Kersting. 4762-4770 [doi]
• Data Driven Threshold and Potential Initialization for Spiking Neural NetworksVelibor Bojkovic, Srinivas Anumasa, Giulia De Masi, Bin Gu, Huan Xiong. 4771-4779 [doi]
• Revisiting the Noise Model of Stochastic Gradient DescentBarak Battash, Lior Wolf, Ofir Lindenbaum. 4780-4788 [doi]
• Warped Diffusion for Latent Differentiation InferenceMasahiro Nakano, Hiroki Sakuma, Ryo Nishikimi, Ryohei Shibue, Takashi Sato, Tomoharu Iwata, Kunio Kashino. 4789-4797 [doi]
• Provable Mutual Benefits from Federated Learning in Privacy-Sensitive DomainsNikita Tsoy, Anna Mihalkova, Teodora N. Todorova, Nikola Konstantinov. 4798-4806 [doi]
• Random Oscillators Network for Time Series ProcessingAndrea Ceni, Andrea Cossu, Maximilian W. Stölzle, Jingyue Liu 0001, Cosimo Della Santina, Davide Bacciu, Claudio Gallicchio. 4807-4815 [doi]
• Mitigating Underfitting in Learning to Defer with Consistent LossesShuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An 0001. 4816-4824 [doi]
• Consistent Hierarchical Classification with A Generalized MetricYuzhou Cao, Lei Feng 0006, Bo An 0001. 4825-4833 [doi]
• SDEs for Minimax OptimizationEnea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Proske, Aurélien Lucchi. 4834-4842 [doi]
• Differentially Private Reward Estimation with Preference FeedbackSayak Ray Chowdhury, Xingyu Zhou 0001, Nagarajan Natarajan. 4843-4851 [doi]
• Differentiable Rendering with Reparameterized Volume SamplingNikita Morozov, Denis Rakitin, Oleg Desheulin, Dmitry P. Vetrov, Kirill Struminsky. 4852-4860 [doi]
• Parameter-Agnostic Optimization under Relaxed SmoothnessFlorian Hübler, Junchi Yang, Xiang Li, Niao He. 4861-4869 [doi]
• Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special CasesRuslan Nazykov, Aleksandr Shestakov, Vladimir Solodkin, Aleksandr Beznosikov, Gauthier Gidel, Alexander V. Gasnikov. 4870-4878 [doi]
• Efficient Conformal Prediction under Data HeterogeneityVincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác 0001, Eric Moulines, Maxim Panov. 4879-4887 [doi]
• Sample-efficient neural likelihood-free Bayesian inference of implicit HMMsSanmitra Ghosh, Paul Birrell, Daniela De Angelis. 4888-4896 [doi]
• Identifying Confounding from Causal Mechanism ShiftsSarah Mameche, Jilles Vreeken, David Kaltenpoth. 4897-4905 [doi]
• Tight Verification of Probabilistic Robustness in Bayesian Neural NetworksBen Batten, Mehran Hosseini, Alessio Lomuscio. 4906-4914 [doi]
• Testing exchangeability by pairwise bettingAytijhya Saha, Aaditya Ramdas. 4915-4923 [doi]