Table of Contents

• Preface [doi]
• Convergence Behavior of an Adversarial Weak Supervision MethodSteven An 0002, Sanjoy Dasgupta. 1-49 [doi]
• Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical SystemsRafael Anderka, Marc Peter Deisenroth, So Takao. 50-76 [doi]
• CSS: Contrastive Semantic Similarities for Uncertainty Quantification of LLMsShuang Ao, Stefan Rueger, Advaith Siddharthan. 77-87 [doi]
• Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance SamplingImad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba. 88-109 [doi]
• Latent Representation Entropy Density for Distribution Shift DetectionFabio Arnez, Daniel Alfonso Montoya Vasquez, Ansgar Radermacher, François Terrier. 110-137 [doi]
• FedAST: Federated Asynchronous Simultaneous TrainingBaris Askin, Pranay Sharma, Carlee Joe-Wong, Gauri Joshi. 138-172 [doi]
• Identifiability of total effects from abstractions of time series causal graphsCharles K. Assaad, Emilie Devijver, Éric Gaussier, Gregor Goessler, Anouar Meynaoui. 173-185 [doi]
• On the Capacitated Facility Location Problem with Scarce ResourcesGennaro Auricchio, Harry J. Clough, Jie Zhang 0008. 186-202 [doi]
• Mitigating Overconfidence in Out-of-Distribution Detection by Capturing Extreme ActivationsMohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Cinà. 203-224 [doi]
• Inference in Probabilistic Answer Set Programs with Imprecise Probabilities via OptimizationDamiano Azzolini, Fabrizio Riguzzi. 225-234 [doi]
• Differentially Private No-regret Exploration in Adversarial Markov Decision ProcessesShaojie Bai, Lanting Zeng, Chengcheng Zhao, Xiaoming Duan, Mohammad Sadegh Talebi, Peng Cheng 0001, Jiming Chen 0001. 235-272 [doi]
• Walking the Values in Bayesian Inverse Reinforcement LearningOndrej Bajgar, Alessandro Abate, Konstantinos Gatsis, Michael A. Osborne. 273-287 [doi]
• Learning Accurate and Interpretable Decision TreesMaria-Florina Balcan, Dravyansh Sharma. 288-307 [doi]
• Towards Bounding Causal Effects under Markov EquivalenceAlexis Bellot. 308-332 [doi]
• Linearly Constrained Gaussian Processes are SkewGPs: application to Monotonic Preference Learning and DesirabilityAlessio Benavoli, Dario Azzimonti. 333-348 [doi]
• MetaCOG: A Heirarchical Probabilistic Model for Learning Meta-Cognitive Visual RepresentationsMarlene Berke, Zhangir Azerbayev, Mario Belledonne, Zenna Tavares, Julian Jara-Ettinger. 349-359 [doi]
• Shedding Light on Large Generative Networks: Estimating Epistemic Uncertainty in Diffusion ModelsLucas Berry, Axel Brando, David Meger. 360-376 [doi]
• Publishing Number of Walks and Katz Centrality under Local Differential PrivacyLouis Betzer, Vorapong Suppakitpaisarn, Quentin Hillebrand. 377-393 [doi]
• Using Autodiff to Estimate Posterior Moments, Marginals and SamplesSam Bowyer, Thomas Heap, Laurence Aitchison. 394-417 [doi]
• Polynomial Semantics of Tractable Probabilistic CircuitsOliver Broadrick, Honghua Zhang, Guy Van den Broeck. 418-429 [doi]
• Products, Abstractions and Inclusions of Causal SpacesSimon Buchholz, Junhyung Park, Bernhard Schölkopf. 430-449 [doi]
• Revisiting Kernel Attention with Correlated Gaussian Process RepresentationLong Minh Bui, Tho Tran Huu, Duy Dinh, Tan Minh Nguyen, Trong Nghia Hoang. 450-470 [doi]
• Sample Average Approximation for Black-Box Variational InferenceJavier Burroni, Justin Domke, Daniel Sheldon. 471-498 [doi]
• Privacy-Aware Randomized Quantization via Linear ProgrammingZhongteng Cai, Xueru Zhang, Mohammad Mahdi Khalili. 499-516 [doi]
• Fair Active Learning in Low-Data RegimesRomain Camilleri, Andrew Wagenmaker, Jamie Morgenstern, Lalit Jain, Kevin Jamieson 0001. 517-531 [doi]
• Multi-Relational Structural EntropyYuwei Cao, Hao Peng 0001, Angsheng Li, Chenyu You, Zhifeng Hao, Philip S. Yu. 532-546 [doi]
• How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural NetworksLuís Felipe P. Cattelan, Danilo Silva. 547-584 [doi]
• QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained ClassifierAditya Challa, Soma S. Dhavala, Snehanshu Saha. 585-602 [doi]
• Generalization and Learnability in Multiple Instance RegressionKushal Chauhan, Rishi Saket, Lorne Applebaum, Ashwinkumar Badanidiyuru, Chandan Giri, Aravindan Raghuveer. 603-618 [doi]
• Gradient descent in matrix factorization: Understanding large initializationHengchao Chen, Xin Chen, Mohamad Elmasri, Qiang Sun. 619-647 [doi]
• Conditional Bayesian QuadratureZonghao Chen, Masha Naslidnyk, Arthur Gretton, François-Xavier Briol. 648-684 [doi]
• Adaptive Time-Stepping Schedules for Diffusion ModelsYuzhu Chen, Fengxiang He, Shi Fu, Xinmei Tian 0001, Dacheng Tao. 685-697 [doi]
• SMuCo: Reinforcement Learning for Visual Control via Sequential Multi-view Total CorrelationTong Cheng, Hang Dong 0004, Lu Wang 0008, Bo Qiao 0001, Qingwei Lin, Saravan Rajmohan, Thomas Moscibroda. 698-717 [doi]
• Inference for Optimal Linear Treatment Regimes in Personalized Decision-makingYuwen Cheng, Shu Yang. 718-735 [doi]
• End-to-end Conditional Robust OptimizationAbhilash Reddy Chenreddy, Erick Delage. 736-748 [doi]
• Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect EstimationYoichi Chikahara, Kansei Ushiyama. 749-762 [doi]
• Fast Interactive Search under a Scale-Free Comparison OracleDaniyar Chumbalov, Lars Klein, Lucas Maystre, Matthias Grossglauser. 763-786 [doi]
• Analysis of Bootstrap and Subsampling in High-dimensional Regularized RegressionLucas Clarté, Adrien Vandenbroucque, Guillaume Dalle, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová. 787-819 [doi]
• Towards Minimax Optimality of Model-based Robust Reinforcement LearningPierre Clavier, Erwan Le Pennec, Matthieu Geist. 820-855 [doi]
• Towards Representation Learning for Weighting Problems in Design-Based Causal InferenceOscar Clivio, Avi Feller, Chris C. Holmes. 856-880 [doi]
• Normalizing Flows for Conformal RegressionNicolò Colombo. 881-893 [doi]
• Power Mean Estimation in Stochastic Monte-Carlo Tree SearchTuan Dam, Odalric-Ambrym Maillard, Emilie Kaufmann. 894-918 [doi]
• Linear Opinion Pooling for Uncertainty Quantification on GraphsClemens Damke, Eyke Hüllermeier. 919-929 [doi]
• Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network MonitoringKhoi Tran Dang, Kevin Delmas, Jérémie Guiochet, Joris Guérin. 930-942 [doi]
• Detecting critical treatment effect bias in small subgroupsPiersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser, Fanny Yang. 943-965 [doi]
• The Real Deal Behind the Artificial Appeal: Inferential Utility of Tabular Synthetic DataAlexander Decruyenaere, Heidelinde Dehaene, Paloma Rabaey, Christiaan Polet, Johan Decruyenaere, Stijn Vansteelandt, Thomas Demeester. 966-996 [doi]
• Discrete Probabilistic Inference as Control in Multi-path EnvironmentsTristan Deleu, Padideh Nouri, Nikolay Malkin, Doina Precup, Yoshua Bengio. 997-1021 [doi]
• On Convergence of Federated Averaging Langevin DynamicsWei Deng 0002, Qian Zhang 0067, Yian Ma, Zhao Song 0002, Guang Lin. 1022-1054 [doi]
• Reflected Schrödinger Bridge for Constrained Generative ModelingWei Deng 0002, Yu Chen, Nicole Tianjiao Yang, Hengrong Du, Qi Feng 0005, Ricky Tian Qi Chen. 1055-1082 [doi]
• Calibrated and Conformal Propensity Scores for Causal Effect EstimationShachi Deshpande, Volodymyr Kuleshov. 1083-1111 [doi]
• Learning to Rank for Active Learning via Multi-Task Bilevel OptimizationZixin Ding, Si Chen, Ruoxi Jia 0001, Yuxin Chen. 1112-1128 [doi]
• End-to-End Learning for Fair Multiobjective Optimization Under UncertaintyMy H. Dinh, James Kotary, Ferdinando Fioretto. 1129-1145 [doi]
• Online Policy Optimization for Robust Markov Decision ProcessJing Dong 0008, Jingwei Li, Baoxiang Wang 0001, Jingzhao Zhang. 1146-1175 [doi]
• Learning Distributionally Robust Tractable Probabilistic Models in Continuous DomainsHailiang Dong, James Amato, Vibhav Gogate, Nicholas Ruozzi. 1176-1188 [doi]
• Bandits with Knapsacks and PredictionsDavide Drago, Andrea Celli, Marek Eliás 0001. 1189-1206 [doi]
• Approximate Bayesian Computation with Path SignaturesJoel Dyer, Patrick Cannon, Sebastian M. Schmon. 1207-1231 [doi]
• Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support RegionsMai Elkady, Thu Bui, Bruno Ribeiro 0001, David I. Inouye. 1232-1256 [doi]
• EntProp: High Entropy Propagation for Improving Accuracy and RobustnessShohei Enomoto. 1257-1270 [doi]
• Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent FidelityMingzhou Fan, Byung-Jun Yoon, Edward R. Dougherty, Nathan M. Urban, Francis J. Alexander, Raymundo Arróyave, Xiaoning Qian. 1271-1293 [doi]
• Center-Based Relaxed Learning Against Membership Inference AttacksXingli Fang, Jung-Eun Kim. 1294-1306 [doi]
• Enhancing Patient Recruitment Response in Clinical Trials: an Adaptive Learning FrameworkXinying Fang, Shouhao Zhou. 1307-1322 [doi]
• Generalized Expected Utility as a Universal Decision Rule - A Step ForwardHélène Fargier, Pierre Pomeret-Coquot. 1323-1338 [doi]
• Last-iterate Convergence Separation between Extra-gradient and Optimism in Constrained Periodic GamesYi Feng, Ping Li, Ioannis Panageas, Xiao Wang 0036. 1339-1370 [doi]
• Guaranteeing Robustness Against Real-World Perturbations In Time Series Classification Using Conformalized Randomized SmoothingNicola Franco, Jakob Spiegelberg, Jeanette Miriam Lorenz, Stephan Günnemann. 1371-1388 [doi]
• Consistency Regularization for Domain Generalization with Logit Attribution MatchingHan Gao, Kaican Li, Weiyan Xie, Zhi Lin, Yongxiang Huang, Luning Wang, Caleb Chen Cao, Nevin L. Zhang. 1389-1407 [doi]
• Uncertainty Estimation with Recursive Feature MachinesDaniel Gedon, Amirhesam Abedsoltan, Thomas B. Schön, Mikhail Belkin. 1408-1437 [doi]
• Bootstrap Your Conversions: Thompson Sampling for Partially Observable Delayed RewardsMarco Gigli, Fabio Stella. 1438-1452 [doi]
• GeONet: a neural operator for learning the Wasserstein geodesicAndrew Gracyk, Xiaohui Chen. 1453-1478 [doi]
• ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-variable Context EncodingDenis A. Gudovskiy, Tomoyuki Okuno, Yohei Nakata. 1479-1490 [doi]
• One Shot Inverse Reinforcement Learning for Stochastic Linear BanditsEtash Guha, Jim James, Krishna Acharya, Vidya Muthukumar, Ashwin Pananjady. 1491-1512 [doi]
• Characterizing Data Point Vulnerability as Average-Case RobustnessTessa Han, Suraj Srinivas, Himabindu Lakkaraju. 1513-1540 [doi]
• No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian ProcessesMinbiao Han, Fengxue Zhang, Yuxin Chen 0001. 1541-1557 [doi]
• Faster Perfect Sampling of Bayesian Network StructuresJuha Harviainen, Mikko Koivisto. 1558-1568 [doi]
• Adjustment Identification Distance: A gadjid for Causal Structure LearningLeonard Henckel, Theo Würtzen, Sebastian Weichwald. 1569-1598 [doi]
• On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBotsChristine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan. 1599-1620 [doi]
• Neural Active Learning Meets the Partial Monitoring FrameworkMaxime Heuillet, Ola Ahmad, Audrey Durand. 1621-1639 [doi]
• Quantum Kernelized BanditsYasunari Hikima, Kazunori Murao, Sho Takemori, Yuhei Umeda. 1640-1657 [doi]
• Recursively-Constrained Partially Observable Markov Decision ProcessesQi Heng Ho, Tyler J. Becker, Benjamin Kraske, Zakariya Laouar, Martin S. Feather, Federico Rossi, Morteza Lahijanian, Zachary Sunberg. 1658-1680 [doi]
• Sound Heuristic Search Value Iteration for Undiscounted POMDPs with Reachability ObjectivesQi Heng Ho, Martin S. Feather, Federico Rossi, Zachary Sunberg, Morteza Lahijanian. 1681-1697 [doi]
• A Global Markov Property for Solutions of Stochastic Difference Equations and the corresponding Full Time GraphsTom Hochsprung, Jakob Runge, Andreas Gerhardus. 1698-1726 [doi]
• Revisiting Convergence of AdaGrad with Relaxed AssumptionsYusu Hong, Junhong Lin. 1727-1750 [doi]
• Equilibrium Computation in Multidimensional Congestion Games: CSP and Learning Dynamics ApproachesMohammad T. Irfan, Hau Chan, Jared Soundy. 1751-1779 [doi]
• Early-Exit Neural Networks with Nested Prediction SetsMetod Jazbec, Patrick Forré, Stephan Mandt, Dan Zhang, Eric T. Nalisnick. 1780-1796 [doi]
• On the Convergence of Hierarchical Federated Learning with Partial Worker ParticipationXiaohan Jiang, Hongbin Zhu. 1797-1824 [doi]
• Adaptive Softmax Trees for Many-Class ClassificationRasul Kairgeldin, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán. 1825-1841 [doi]
• Towards Scalable Bayesian Transformers: Investigating stochastic subset selection for NLPPeter Johannes Tejlgaard Kampen, Gustav Ragnar Stoettrup Als, Michael Riis Andersen. 1842-1862 [doi]
• Low-rank Matrix Bandits with Heavy-tailed RewardsYue Kang 0002, Cho-Jui Hsieh, Thomas Chun Man Lee. 1863-1889 [doi]
• Cost-Sensitive Uncertainty-Based Failure Recognition for Object DetectionMoussa Kassem Sbeyti, Michelle Karg, Christian Wirth 0001, Nadja Klein, Sahin Albayrak. 1890-1900 [doi]
• Probabilities of Causation for Continuous and Vector VariablesYuta Kawakami, Manabu Kuroki, Jin Tian. 1901-1921 [doi]
• Identification and Estimation of Conditional Average Partial Causal Effects via Instrumental VariableYuta Kawakami, Manabu Kuroki, Jin Tian. 1922-1952 [doi]
• Targeted Reduction of Causal ModelsArmin Kekic, Bernhard Schölkopf, Michel Besserve. 1953-1980 [doi]
• Active Learning Framework for Incomplete NetworksTung Khong, Cong Tran, Cuong Pham 0001. 1981-1998 [doi]
• Causal Discovery with Deductive Reasoning: One Less ProblemJonghwan Kim, Inwoo Hwang, Sanghack Lee. 1999-2017 [doi]
• ILP-FORMER: Solving Integer Linear Programming with Sequence to Multi-Label LearningShufeng Kong, Caihua Liu, Carla Gomes 0001. 2018-2028 [doi]
• How Inverse Conditional Flows Can Serve as a Substitute for Distributional RegressionLucas Kook, Chris Kolb, Philipp Schiele, Daniel Dold, Marcel Arpogaus, Cornelius Fritz, Philipp F. M. Baumann, Philipp Kopper, Tobias Pielok, Emilio Dorigatti, David Rügamer. 2029-2046 [doi]
• Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value DistributionsPatrick K. Kuiper, Ali-Hasan, Wenhao Yang, Yuting Ng, Hoda Bidkhori, Jose H. Blanchet, Vahid Tarokh. 2047-2063 [doi]
• Optimization Framework for Semi-supervised Attributed Graph CoarseningManoj Kumar, Subhanu Halder, Archit Kane, Ruchir Gupta, Sandeep Kumar. 2064-2075 [doi]
• Efficient Monte Carlo Tree Search via On-the-Fly State-Conditioned Action AbstractionYunhyeok Kwak, Inwoo Hwang, Dooyoung Kim, Sanghack Lee, Byoung-Tak Zhang. 2076-2093 [doi]
• DataSP: A Differential All-to-All Shortest Path Algorithm for Learning Costs and Predicting Paths with ContextAlan A. Lahoud, Erik Schaffernicht, Johannes A. Stork. 2094-2112 [doi]
• Quantifying Local Model Validity using Active LearningSven Lämmle, Can Bogoclu, Robert Vosshall, Anselm Haselhoff, Dirk Roos. 2113-2135 [doi]
• Common Event Tethering to Improve Prediction of Rare Clinical EventsQuinn Lanners, Qin Weng, Marie-Louise Meng, Matthew M. Engelhard. 2136-2162 [doi]
• Support Recovery in Sparse PCA with General Missing DataHanbyul Lee 0001, Qifan Song, Jean Honorio. 2163-2187 [doi]
• A General Identification Algorithm For Data Fusion Problems Under Systematic SelectionJaron Jia Rong Lee, AmirEmad Ghassami, Ilya Shpitser. 2188-2204 [doi]
• On the Inductive Biases of Demographic Parity-based Fair Learning AlgorithmsHaoyu Lei, Amin Gohari, Farzan Farnia. 2205-2225 [doi]
• Label Consistency-based Worker Filtering for CrowdsourcingJiao Li, Liangxiao Jiang, Chaoqun Li 0001, Wenjun Zhang 0012. 2226-2237 [doi]
• Learning from Crowds with Dual-View K-Nearest NeighborJiao Li, Liangxiao Jiang, Xue Wu, Wenjun Zhang 0012. 2238-2249 [doi]
• Optimizing Language Models for Human Preferences is a Causal Inference ProblemVictoria Lin 0001, Eli Ben-Michael, Louis-Philippe Morency. 2250-2270 [doi]
• Transductive and Inductive Outlier Detection with Robust AutoencodersOfir Lindenbaum, Yariv Aizenbud, Yuval Kluger. 2271-2293 [doi]
• Hybrid CtrlFormer: Learning Adaptive Search Space Partition for Hybrid Action Control via Transformer-based Monte Carlo Tree SearchJiashun Liu, Xiaotian Hao, Jianye Hao, Yan Zheng 0002, Yujing Hu, Changjie Fan, Tangjie Lv, Zhipeng Hu. 2294-2308 [doi]
• Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language ModelsXinyang Liu, Dongsheng Wang 0003, Bowei Fang, Miaoge Li, Yishi Xu, Zhibin Duan, Bo Chen 0001, Mingyuan Zhou. 2309-2330 [doi]
• Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded VarianceJorge Loría, Anindya Bhadra. 2331-2349 [doi]
• Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome PairsJacqueline R. M. A. Maasch, Weishen Pan, Shantanu Gupta, Volodymyr Kuleshov, Kyra Gan, Fei Wang. 2350-2382 [doi]
• Identifying Causal Changes Between Linear Structural Equation ModelsVineet Malik, Kevin Bello, Asish Ghoshal, Jean Honorio. 2383-2398 [doi]
• BEARS Make Neuro-Symbolic Models Aware of their Reasoning ShortcutsEmanuele Marconato, Samuele Bortolotti, Emile van Krieken, Antonio Vergari, Andrea Passerini, Stefano Teso. 2399-2433 [doi]
• Amortized Variational Inference: When and Why?Charles C. Margossian, David M. Blei. 2434-2449 [doi]
• Learning relevant contextual variables within Bayesian optimizationJulien Martinelli, Ayush Bharti, Armi Tiihonen, S. T. John, Louis Filstroff, Sabina J. Sloman, Patrick Rinke, Samuel Kaski. 2450-2470 [doi]
• Identifying Homogeneous and Interpretable Groups for Conformal PredictionNatalia Martinez Gil, Dhaval Patel 0002, Chandra Reddy, Giridhar Ganapavarapu, Roman Vaculín, Jayant Kalagnanam. 2471-2485 [doi]
• Learning Causal Abstractions of Linear Structural Causal ModelsRiccardo Massidda, Sara Magliacane, Davide Bacciu. 2486-2515 [doi]
• Knowledge Intensive Learning of Credal NetworksSaurabh Mathur 0002, Alessandro Antonucci 0001, Sriraam Natarajan. 2516-2526 [doi]
• Quantization of Large Language Models with an Overdetermined BasisDaniil Merkulov, Daria Cherniuk, Alexander Rudikov, Ivan V. Oseledets, Ekaterina A. Muravleva, Aleksandr Mikhalev, Boris Kashin. 2527-2536 [doi]
• Invariant Causal Prediction with Local ModelsAlexander Mey, Rui Manuel Castro. 2537-2559 [doi]
• Characterising Interventions in Causal GamesManuj Mishra, James Fox, Michael J. Wooldridge. 2560-2572 [doi]
• Approximation Algorithms for Observer Aware MDPsShuwa Miura, Olivier Buffet, Shlomo Zilberstein. 2573-2586 [doi]
• Evaluating Bayesian deep learning for radio galaxy classificationDevina Mohan, Anna M. M. Scaife. 2587-2597 [doi]
• Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision ProcessesSang Bin Moon, Abolfazl Hashemi. 2598-2622 [doi]
• Partial identification of the maximum mean discrepancy with mismeasured dataRon Nafshi, Maggie Makar. 2623-2645 [doi]
• General Markov Model for Solving Patrolling GamesAndrzej Nagórko, Marcin Waniek, Malgorzata Róg, Michal Tomasz Godziszewski, Barbara Rosiak, Tomasz Pawel Michalak. 2646-2669 [doi]
• Efficient Interactive Maximization of BP and Weakly Submodular ObjectivesAdhyyan Narang, Omid Sadeghi, Lillian J. Ratliff, Maryam Fazel, Jeff A. Bilmes. 2670-2699 [doi]
• Neural Architecture Search Finds Robust Models by Knowledge DistillationUtkarsh Nath, Yancheng Wang, Yingzhen Yang. 2700-2715 [doi]
• Extremely Greedy Equivalence SearchAchille Nazaret, David M. Blei. 2716-2745 [doi]
• A Generalized Bayesian Approach to Distribution-on-Distribution RegressionTin Lok James Ng. 2746-2765 [doi]
• Cold-start Recommendation by Personalized Embedding Region ElicitationHieu Trung Nguyen, Duy Nguyen, Khoa D. Doan, Viet Anh Nguyen. 2766-2786 [doi]
• Finite-Time Analysis of Three-Timescale Constrained Actor-Critic and Constrained Natural Actor-Critic AlgorithmsPrashansa Panda, Shalabh Bhatnagar. 2787-2834 [doi]
• Quantifying Representation Reliability in Self-Supervised Learning ModelsYoung-Jin Park, Hao Wang, Shervin Ardeshir, Navid Azizan. 2835-2860 [doi]
• Value-Based Abstraction Functions for Abstraction SamplingBobak Pezeshki, Kalev Kask, Alexander Ihler, Rina Dechter. 2861-2901 [doi]
• Non-stationary Domain Generalization: Theory and AlgorithmThai-Hoang Pham, Xueru Zhang, Ping Zhang 0016. 2902-2927 [doi]
• Zero Inflation as a Missing Data Problem: a Proxy-based ApproachTrung Phung, Jaron J. R. Lee, Opeyemi Oladapo-Shittu, Eili Y. Klein, Ayse Pinar Gurses, Susan M. Hannum, Kimberly Weems, Jill A. Marsteller, Sara E. Cosgrove, Sara C. Keller, Ilya Shpitser. 2928-2955 [doi]
• DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distributionMatías P. Pizarro B., Dorothea Kolossa, Asja Fischer. 2956-2988 [doi]
• Neural Optimal Transport with Lagrangian CostsAram-Alexandre Pooladian, Carles Domingo-Enrich, Ricky T. Q. Chen, Brandon Amos. 2989-3003 [doi]
• χSPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid DomainsHarsh Poonia, Moritz Willig, Zhongjie Yu 0001, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami. 3004-3020 [doi]
• Graph Feedback Bandits with Similar ArmsHan Qi, Guo Fei 0010, Li Zhu. 3021-3040 [doi]
• Performative Reinforcement Learning in Gradually Shifting EnvironmentsBen Rank, Stelios Triantafyllou, Debmalya Mandal, Goran Radanovic. 3041-3075 [doi]
• Decision-Focused Evaluation of Worst-Case Distribution ShiftKevin Ren, Yewon Byun, Bryan Wilder. 3076-3093 [doi]
• To smooth a cloud or to pin it down: Expressiveness guarantees and insights on score matching in denoising diffusion modelsTeodora Reu, Francisco Vargas 0001, Anna Kerekes, Michael M. Bronstein. 3094-3120 [doi]
• Anomaly Detection with Variance Stabilized Density EstimationAmit Rozner, Barak Battash, Henry Li, Lior Wolf, Ofir Lindenbaum. 3121-3137 [doi]
• A Graph Theoretic Approach for Preference Learning with Feature InformationAadirupa Saha, Arun Rajkumar. 3138-3158 [doi]
• Label-wise Aleatoric and Epistemic Uncertainty QuantificationYusuf Sale, Paul Hofman, Timo Löhr, Lisa Wimmer, Thomas Nagler, Eyke Hüllermeier. 3159-3179 [doi]
• Unsupervised Feature Selection towards Pattern Discrimination PowerWangduk Seo, Jaesung Lee 0001. 3180-3197 [doi]
• Cooperative Meta-Learning with Gradient AugmentationJongyun Shin, Seungjin Han, Jangho Kim. 3198-3210 [doi]
• Response Time Improves Gaussian Process Models for Perception and PreferencesMichael Shvartsman, Benjamin Letham, Eytan Bakshy, Stephen Keeley. 3211-3226 [doi]
• BanditQ: Fair Bandits with Guaranteed RewardsAbhishek Sinha. 3227-3244 [doi]
• Bayesian Active Learning in the Presence of Nuisance ParametersSabina J. Sloman, Ayush Bharti, Julien Martinelli, Samuel Kaski. 3245-3263 [doi]
• Memorization Capacity for Additive Fine-Tuning with Small ReLU NetworksJy-yong Sohn, Dohyun Kwon 0002, Seoyeon An, Kangwook Lee 0001. 3264-3278 [doi]
• Computing Low-Entropy Couplings for Large-Support DistributionsSamuel Sokota, Dylan Sam, Christian Schröder de Witt, Spencer Compton, Jakob N. Foerster, J. Zico Kolter. 3279-3298 [doi]
• Multi-layer random features and the approximation power of neural networksRustem Takhanov. 3299-3322 [doi]
• A Homogenization Approach for Gradient-Dominated Stochastic OptimizationJiyuan Tan, Chenyu Xue, Chuwen Zhang, Qi Deng, Dongdong Ge, Yinyu Ye 0001. 3323-3344 [doi]
• Localised Natural Causal Learning Algorithms for Weak Consistency ConditionsKai Z. Teh, Kayvan Sadeghi, Terry Soo. 3345-3355 [doi]
• Fast Reliability Estimation for Neural Networks with Adversarial Attack-Driven Importance SamplingKarim Tit, Teddy Furon. 3356-3367 [doi]
• Bayesian Pseudo-Coresets via Contrastive DivergencePiyush Tiwary, Kumar Shubham, Vivek Kashyap, Prathosh A. P.. 3368-3390 [doi]
• Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and Posterior Value Optimisation in Finite-State MDPsFilippo Valdettaro, Aldo Faisal. 3391-3409 [doi]
• Efficiently Deciding Algebraic Equivalence of Bow-Free Acyclic Path DiagramsThijs van Ommen. 3410-3424 [doi]
• Random Linear Projections Loss for Hyperplane-Based Optimization in Neural NetworksShyam Venkatasubramanian, Ahmed Aloui, Vahid Tarokh. 3425-3447 [doi]
• Group Fairness in Predict-Then-Optimize Settings for Restless BanditsShresth Verma, Yunfan Zhao, Sanket Shah, Niclas Boehmer, Aparna Taneja, Milind Tambe. 3448-3469 [doi]
• Model-Free Robust Reinforcement Learning with Sample Complexity AnalysisYudan Wang, Shaofeng Zou, Yue Wang 0068. 3470-3513 [doi]
• Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal StatesZiqiao Wang, Yongyi Mao. 3514-3539 [doi]
• Pure Exploration in Asynchronous Federated BanditsZichen Wang, Chuanhao Li, Chenyu Song, Lianghui Wang, Quanquan Gu, Huazheng Wang. 3540-3570 [doi]
• Metric Learning from Limited Pairwise Preference ComparisonsZhi Wang 0013, Geelon So, Ramya Korlakai Vinayak. 3571-3602 [doi]
• AutoDrop: Training Deep Learning Models with Automatic Learning Rate DropJing Wang, Yunfei Teng, Anna Choromanska. 3603-3629 [doi]
• Bias-aware Boolean Matrix Factorization Using Disentangled Representation LearningXiao Wang 0012, Jia Wang, Tong Zhao 0002, Yijie Wang, Nan Zhang, Yong Zang, Sha Cao, Chi Zhang 0021. 3630-3642 [doi]
• Beyond Dirichlet-based Models: When Bayesian Neural Networks Meet Evidential Deep LearningHanjing Wang, Qiang Ji. 3643-3665 [doi]
• Stein Random Feature RegressionHouston Warren, Rafael Oliveira 0001, Fabio T. Ramos 0001. 3666-3688 [doi]
• Bounding causal effects with leaky instrumentsDavid S. Watson, Jordan Penn, Lee M. Gunderson, Gecia Bravo Hermsdorff, Afsaneh Mastouri, Ricardo Silva 0001. 3689-3710 [doi]
• Robust Entropy Search for Safe Efficient Bayesian OptimizationDorina Weichert, Alexander Kister, Sebastian Houben, Patrick Link, Gunar Ernis. 3711-3729 [doi]
• Hidden Population Estimation with Indirect Inference and Auxiliary InformationJustin Weltz, Eric Laber, Alexander Volfovsky. 3730-3746 [doi]
• GCVR: Reconstruction from Cross-View Enable Sufficient and Robust Graph Contrastive LearningQianlong Wen, Zhongyu Ouyang, Chunhui Zhang, Yiyue Qian, Chuxu Zhang, Yanfang Ye 0001. 3747-3764 [doi]
• Understanding Pathologies of Deep Heteroskedastic RegressionEliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt. 3765-3790 [doi]
• Functional Wasserstein Bridge Inference for Bayesian Deep LearningMengjing Wu, Junyu Xuan, Jie Lu 0001. 3791-3815 [doi]
• RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR PredictionSongli Wu, Liang Du, Jiaqi Yang, Yuai Wang, De-Chuan Zhan, Shuang Zhao, Zixun Sun. 3816-3828 [doi]
• Pix2Code: Learning to Compose Neural Visual Concepts as ProgramsAntonia Wüst, Wolfgang Stammer, Quentin Delfosse, Devendra Singh Dhami, Kristian Kersting. 3829-3852 [doi]
• Base Models for Parabolic Partial Differential EquationsXingzi Xu, Ali-Hasan, Jie Ding 0002, Vahid Tarokh. 3853-3878 [doi]
• α-Former: Local-Feature-Aware (L-FA) TransformerZhi Xu, Bin Sun 0002, Yue Bai, Yun Fu 0001. 3879-3892 [doi]
• Functional Wasserstein Variational Policy OptimizationJunyu Xuan, Mengjing Wu, Zihe Liu, Jie Lu 0001. 3893-3911 [doi]
• Investigating the Impact of Model Width and Density on Generalization in Presence of Label NoiseYihao Xue, Kyle Whitecross, Baharan Mirzasoleiman. 3912-3935 [doi]
• Graph Contrastive Learning under Heterophily via Graph FiltersWenhan Yang, Baharan Mirzasoleiman. 3936-3955 [doi]
• Statistical and Causal Robustness for Causal Null Hypothesis TestsJunhui Yang, Rohit Bhattacharya, Youjin Lee, Ted Westling. 3956-3978 [doi]
• On Hardware-efficient Inference in Probabilistic CircuitsLingyun Yao, Martin Trapp 0001, Jelin Leslin, Gaurav Singh 0005, Peng Zhang 0028, Karthekeyan Periasamy, Martin Andraud. 3979-3996 [doi]
• Masking the Unknown: Leveraging Masked Samples for Enhanced Data AugmentationXun Yao, Zijian Huang 0012, Xinrong Hu, Jie Yang 0009, Yi Guo 0001. 3997-4010 [doi]
• Domain Adaptation with Cauchy-Schwarz DivergenceWenzhe Yin, Shujian Yu, Yicong Lin, Jie Liu 0043, Jan-Jakob Sonke, Efstratios Gavves. 4011-4040 [doi]
• Offline Reward Perturbation Boosts Distributional Shift in Online RLZishun Yu, Siteng Kang, Xinhua Zhang. 4041-4055 [doi]
• Decentralized Online Learning in General-Sum Stackelberg GamesYaolong Yu, Haipeng Chen 0001. 4056-4077 [doi]
• Probabilistic reconciliation of mixed-type hierarchical time seriesLorenzo Zambon, Dario Azzimonti, Nicolò Rubattu, Giorgio Corani. 4078-4095 [doi]
• Dirichlet Continual Learning: Tackling Catastrophic Forgetting in NLPMin Zeng, Haiqin Yang, Wei Xue, Qifeng Liu, Yike Guo. 4096-4108 [doi]
• Causally Abstracted Multi-armed BanditsFabio Massimo Zennaro, Nicholas Bishop, Joel Dyer, Yorgos Felekis, Anisoara Calinescu, Michael J. Wooldridge, Theodoros Damoulas. 4109-4139 [doi]
• Partial Identification with Proxy of Latent Confoundings via Sum-of-ratios Fractional ProgrammingZhiheng Zhang, Xinyan Su. 4140-4172 [doi]
• Decentralized Two-Sided Bandit Learning in Matching MarketYirui Zhang, Zhixuan Fang. 4173-4191 [doi]
• Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling ProblemCong Zhang, Zhiguang Cao, Yaoxin Wu, Wen Song, Jing Sun. 4192-4208 [doi]
• Neighbor Similarity and Multimodal Alignment based Product Recommendation StudyZhiqiang Zhang, Yongqiang Jiang, Qian Gao, Zhipeng Wang. 4209-4218 [doi]
• Exploring High-dimensional Search Space via Voronoi Graph TraversingAidong Zhao, Xuyang Zhao, Tianchen Gu, Zhaori Bi, Xinwei Sun 0001, Changhao Yan, Fan Yang 0001, Dian Zhou, Xuan Zeng 0001. 4219-4236 [doi]
• Trusted re-weighting for label distribution learningZhuoran Zheng, Chen Wu 0006, Yeying Jin, Xiuyi Jia. 4237-4249 [doi]
• Approximate Kernel Density Estimation under Metric-based Local Differential PrivacyYi Zhou, Yanhao Wang 0001, Long Teng, Qiang Huang, Cen Chen 0001. 4250-4270 [doi]