Table of Contents

• Additive Model Boosting: New Insights and Path(ologie)sRickmer Schulte, David Rügamer. 1-9 [doi]
• Paths and Ambient Spaces in Neural Loss LandscapesDaniel Dold, Julius Kobialka, Nicolai Palm, Emanuel Sommer, David Rügamer, Oliver Dürr. 10-18 [doi]
• Automatically Adaptive Conformal Risk ControlVincent Blot, Anastasios Nikolas Angelopoulos, Michael I. Jordan, Nicolas J.-B. Brunel. 19-27 [doi]
• Cost-aware simulation-based inferenceAyush Bharti, Daolang Huang, Samuel Kaski, François-Xavier Briol. 28-36 [doi]
• Generalized Criterion for Identifiability of Additive Noise Models Using MajorizationAramayis Dallakyan, Yang Ni. 37-45 [doi]
• Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel-Young Loss Perspective and Gap-Dependent Regret AnalysisShinsaku Sakaue, Han Bao 0002, Taira Tsuchiya. 46-54 [doi]
• Locally Private Estimation with Public FeaturesYuheng Ma 0001, Ke Jia, Hanfang Yang. 55-63 [doi]
• A Family of Distributions of Random Subsets for Controlling Positive and Negative DependenceTakahiro Kawashima, Hideitsu Hino. 64-72 [doi]
• Lower Bounds for Time-Varying Kernelized BanditsXu Cai, Jonathan Scarlett. 73-81 [doi]
• Randomized Iterative Solver as Iterative Refinement: A Simple Fix Towards Backward StabilityRuihan Xu 0005, Yiping Lu. 82-90 [doi]
• Flexible Copula-Based Mixed Models in Deep Learning: A Scalable Approach to Arbitrary MarginalsGiora Simchoni, Saharon Rosset. 91-99 [doi]
• Bayesian Inference in Recurrent Explicit Duration Switching Linear Dynamical SystemsMikolaj Slupinski. 100-108 [doi]
• ClusterSC: Advancing Synthetic Control with Donor SelectionSaeyoung Rho, Andrew Tang, Noah Bergam, Rachel Cummings, Vishal Misra. 109-117 [doi]
• Efficient Estimation of a Gaussian Mean with Local Differential PrivacyKalinin Nikita, Lukas Steinberger. 118-126 [doi]
• Credal Two-Sample Tests of Epistemic UncertaintySiu Lun Chau, Antonin Schrab, Arthur Gretton, Dino Sejdinovic, Krikamol Muandet. 127-135 [doi]
• Bayesian Off-Policy Evaluation and Learning for Large Action SpacesImad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba. 136-144 [doi]
• On the Convergence of Locally Adaptive and Scalable Diffusion-Based Sampling Methods for Deep Bayesian Neural Network PosteriorsTim Rensmeyer, Oliver Niggemann. 145-153 [doi]
• Fine-Tuning with Uncertainty-Aware Priors Makes Vision and Language Foundation Models More ReliableTim G. J. Rudner, Xiang Pan, Yucen Lily Li, Ravid Shwartz-Ziv, Andrew Gordon Wilson. 154-162 [doi]
• Optimising Clinical Federated Learning through Mode Connectivity-based Model AggregationAnshul Thakur, Soheila Molaei, Patrick Schwab, Danielle Belgrave, Kim Branson 0001, David A. Clifton. 163-171 [doi]
• S-CFE: Simple Counterfactual ExplanationsShpresim Sadiku, Moritz Wagner 0002, Sai Ganesh Nagarajan, Sebastian Pokutta. 172-180 [doi]
• A Unifying Framework for Action-Conditional Self-Predictive Reinforcement LearningKhimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland 0001, Nicolas Heess, Diana L. Borsa, Arthur Guez, Will Dabney. 181-189 [doi]
• Estimation of Large Zipfian Distributions with Sort and SnapPeter Matthew Jacobs, Anirban Bhattacharya, Debdeep Pati, Lekha Patel, Jeff M. Phillips. 190-198 [doi]
• Relating Piecewise Linear Kolmogorov Arnold Networks to ReLU NetworksNandi Schoots, Mattia Jacopo Villani, Niels uit de Bos. 199-207 [doi]
• β-th order Acyclicity Derivatives for DAG LearningMadhumitha Shridharan, Garud Iyengar. 208-216 [doi]
• Conditional Generative Learning from Invariant Representations in Multi-Source: Robustness and EfficiencyGuojun Zhu, Sanguo Zhang, Mingyang Ren. 217-225 [doi]
• Harnessing the Power of Vicinity-Informed Analysis for Classification under Covariate ShiftMitsuhiro Fujikawa, Youhei Akimoto, Jun Sakuma, Kazuto Fukuchi. 226-234 [doi]
• Bayesian Gaussian Process ODEs via Double Normalizing FlowsJian Xu 0021, Shian Du, Junmei Yang, Xinghao Ding, Delu Zeng, John Paisley. 235-243 [doi]
• The Local Learning Coefficient: A Singularity-Aware Complexity MeasureEdmund Lau, Zach Furman, George Wang, Daniel Murfet, Susan Wei. 244-252 [doi]
• Density Ratio Estimation via Sampling along Generalized Geodesics on Statistical ManifoldsMasanari Kimura, Howard D. Bondell. 253-261 [doi]
• Choice is what matters after AttentionChenhan Fu, Guoming Wang, Juncheng Li 0006, Rongxing Lu, Siliang Tang. 262-270 [doi]
• The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size ControlMathieu Besançon, Sebastian Pokutta, Elias Samuel Wirth. 271-279 [doi]
• Accelerated Methods for Riemannian Min-Max Optimization Ensuring Bounded Geometric PenaltiesDavid Martínez-Rubio, Christophe Roux, Christopher Criscitiello, Sebastian Pokutta. 280-288 [doi]
• Almost linear time differentially private release of synthetic graphsZongrui Zou, Jingcheng Liu 0001, Jalaj Upadhyay. 289-297 [doi]
• Adversarial Training in High-Dimensional Regression: Generated Data and Neural NetworksYue Xing. 298-306 [doi]
• A Bias-Variance Decomposition for Ensembles over Multiple Synthetic DatasetsOssi Räisä, Antti Honkela. 307-315 [doi]
• Approximate information maximization for bandit gamesAlex Barbier-Chebbah, Christian L. Vestergaard, Jean-Baptiste Masson, Etienne Boursier. 316-324 [doi]
• Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VIAbhinav Agrawal 0001, Justin Domke. 325-333 [doi]
• Generalization Lower Bounds for GD and SGD in Smooth Stochastic Convex OptimizationPeiyuan Zhang, Jiaye Teng, Jingzhao Zhang. 334-342 [doi]
• Learning in Herding Mean Field Games: Single-Loop Algorithm with Finite-Time Convergence AnalysisSihan Zeng, Sujay Bhatt, Alec Koppel, Sumitra Ganesh. 343-351 [doi]
• Strong Screening Rules for Group-based SLOPE ModelsFabio Feser, Marina Evangelou. 352-360 [doi]
• Infinite-Horizon Reinforcement Learning with Multinomial Logit Function ApproximationJaehyun Park, Junyeop Kwon, Dabeen Lee. 361-369 [doi]
• Constrained Multi-objective Bayesian Optimization through Optimistic Constraints EstimationDiantong Li, Fengxue Zhang, Chong Liu 0007, Yuxin Chen. 370-378 [doi]
• Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured BanditsNicolas Nguyen, Imad Aouali, András György 0001, Claire Vernade. 379-387 [doi]
• Nyström Kernel Stein DiscrepancyFlorian Kalinke, Zoltán Szabó 0001, Bharath K. Sriperumbudur. 388-396 [doi]
• Some Targets Are Harder to Identify than Others: Quantifying the Target-dependent Membership LeakageAchraf Azize, Debabrota Basu. 397-405 [doi]
• Near-Optimal Algorithm for Non-Stationary Kernelized BanditsShogo Iwazaki, Shion Takeno. 406-414 [doi]
• No-Regret Bayesian Optimization with Stochastic Observation FailuresShogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Kota Matsui, Yu Inatsu. 415-423 [doi]
• Nonparametric Factor Analysis and BeyondYujia Zheng 0001, Yang Liu 0018, Jiaxiong Yao, Yingyao Hu, Kun Zhang 0001. 424-432 [doi]
• Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy MaximizationDeep Chakraborty, Yann LeCun, Tim G. J. Rudner, Erik G. Learned-Miller. 433-441 [doi]
• Scalable Inference for Bayesian Multinomial Logistic-Normal Dynamic Linear ModelsManan Saxena, Tinghua Chen, Justin D. Silverman. 442-450 [doi]
• Inverse Optimization with Prediction Market: A Characterization of Scoring Rules for Elciting System StatesHan Bao 0002, Shinsaku Sakaue. 451-459 [doi]
• HAVER: Instance-Dependent Error Bounds for Maximum Mean Estimation and Applications to Q-Learning and Monte Carlo Tree SearchTuan Nguyen, Jay Barrett, Kwang-Sung Jun. 460-468 [doi]
• Ant Colony Sampling with GFlowNets for Combinatorial OptimizationMinsu Kim 0004, Sanghyeok Choi, Hyeonah Kim, Jiwoo Son, Jinkyoo Park, Yoshua Bengio. 469-477 [doi]
• Function-Space MCMC for Bayesian Wide Neural NetworksLucia Pezzetti, Stefano Favaro, Stefano Peluchetti. 478-486 [doi]
• A Theoretical Framework for Preventing Class Collapse in Supervised Contrastive LearningChungpa Lee, Jeongheon Oh, Kibok Lee 0003, Jy-yong Sohn. 487-495 [doi]
• Signed Graph Autoencoder for Explainable and Polarization-Aware Network EmbeddingsNikolaos Nakis, Chrysoula Kosma, Giannis Nikolentzos, Michail Chatzianastasis, Iakovos Evdaimon, Michalis Vazirgiannis. 496-504 [doi]
• On the Asymptotic Mean Square Error Optimality of Diffusion ModelsBenedikt Fesl, Benedikt Böck, Florian Strasser, Michael Baur, Michael Joham, Wolfgang Utschick. 505-513 [doi]
• Adaptive Extragradient Methods for Root-finding Problems under Relaxed AssumptionsYang Luo, Michael J. O'Neill. 514-522 [doi]
• Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple InputsChenyang Li, Yingyu Liang, Zhenmei Shi, Zhao Song 0002, Tianyi Zhou 0011. 523-531 [doi]
• Signature Isolation ForestMarta Campi, Guillaume Staerman, Gareth W. Peters, Tomoko Masui. 532-540 [doi]
• Elastic Representation: Mitigating Spurious Correlations for Group RobustnessTao Wen 0007, Zihan Wang, Quan Zhang, Qi Lei. 541-549 [doi]
• Scalable spectral representations for multiagent reinforcement learning in network MDPsZhaolin Ren, Runyu Zhang 0001, Bo Dai 0001, Na Li 0002. 550-558 [doi]
• Bridging Domains with Approximately Shared FeaturesZiliang Samuel Zhong, Xiang Pan, Qi Lei. 559-567 [doi]
• Epistemic Uncertainty and Excess Risk in Variational InferenceFutoshi Futami. 568-576 [doi]
• Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal LearningJiaru Zhang, Rui Ding 0001, Qiang Fu 0015, Bojun Huang, Zizhen Deng, Yang Hua 0001, Haibing Guan, Shi Han, Dongmei Zhang 0001. 577-585 [doi]
• Selecting the Number of Communities for Weighted Degree-Corrected Stochastic Block ModelsYucheng Liu, Xiaodong Li. 586-594 [doi]
• Empirical Error Estimates for Graph SparsificationSiyao Wang, Miles E. Lopes. 595-603 [doi]
• On the Geometry and Optimization of Polynomial Convolutional NetworksVahid Shahverdi, Giovanni Luca Marchetti, Kathlén Kohn. 604-612 [doi]
• Data Reconstruction Attacks and Defenses: A Systematic EvaluationSheng Liu, Zihan Wang, Yuxiao Chen, Qi Lei. 613-621 [doi]
• Locally Private Sampling with Public DataBehnoosh Zamanlooy, Mario Díaz, Shahab Asoodeh. 622-630 [doi]
• Reliable and Scalable Variable Importance Estimation via Warm-start and Early StoppingZexuan Sun, Garvesh Raskutti. 631-639 [doi]
• Reinforcement Learning for Adaptive MCMCCongye Wang, Wilson Ye Chen, Heishiro Kanagawa, Chris J. Oates. 640-648 [doi]
• Prediction-Centric Uncertainty Quantification via MMDZheyang Shen, Jeremias Knoblauch, Samuel Power, Chris J. Oates. 649-657 [doi]
• Harnessing Causality in Reinforcement Learning with Bagged Decision TimesDaiqi Gao, Hsin-Yu Lai, Predrag Klasnja, Susan A. Murphy. 658-666 [doi]
• Learning the Pareto Front Using Bootstrapped Observation SamplesWonyoung Kim, Garud Iyengar, Assaf Zeevi. 667-675 [doi]
• FedBaF: Federated Learning Aggregation Biased by a Foundation ModelJong-Ik Park, Srinivasa Pranav, José M. F. Moura, Carlee Joe-Wong. 676-684 [doi]
• A Generalized Theory of Mixup for Structure-Preserving Synthetic DataChungpa Lee, Jongho Im, Joseph H. T. Kim. 685-693 [doi]
• On the Sample Complexity of Next-Token PredictionOguz Kaan Yüksel, Nicolas Flammarion. 694-702 [doi]
• Amortized Probabilistic Conditioning for Optimization, Simulation and InferencePaul Edmund Chang, Nasrulloh Ratu Bagus Satrio Loka, Daolang Huang, Ulpu Remes, Samuel Kaski, Luigi Acerbi. 703-711 [doi]
• Steering No-Regret Agents in MFGs under Model UncertaintyLeo Widmer, Jiawei Huang, Niao He. 712-720 [doi]
• Bridging Multiple Worlds: Multi-marginal Optimal Transport for Causal Partial-identification ProblemZijun Gao, Shu Ge, Jian Qian. 721-729 [doi]
• The Polynomial Iteration Complexity for Variance Exploding Diffusion Models: Elucidating SDE and ODE SamplersRuofeng Yang, Bo Jiang, Shuai Li 0010. 730-738 [doi]
• To Give or Not to Give? The Impacts of Strategically Withheld RecourseYatong Chen, Andrew Estornell, Yevgeniy Vorobeychik, Yang Liu 0018. 739-747 [doi]
• Optimal estimation of linear non-Gaussian structure equation modelsSunmin Oh, Seungsu Han, Gunwoong Park. 748-756 [doi]
• Stein Boltzmann Sampling: A Variational Approach for Global OptimizationGaëtan Serré, Argyris Kalogeratos, Nicolas Vayatis. 757-765 [doi]
• Learning signals defined on graphs with optimal transport and Gaussian process regressionRaphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber. 766-774 [doi]
• Score matching for bridges without learning time-reversalsElizabeth Louise Baker, Moritz Schauer, Stefan Sommer. 775-783 [doi]
• Safe exploration in reproducing kernel Hilbert spacesAbdullah Tokmak, Kiran G. Krishnan, Thomas B. Schön, Dominik Baumann. 784-792 [doi]
• V-information Growth: A Fresh Perspective on Shared InformationRohan Ghosh, Mehul Motani. 793-801 [doi]
• On Tradeoffs in Learning-Augmented AlgorithmsZiyad Benomar, Vianney Perchet. 802-810 [doi]
• Cubic regularized subspace Newton for non-convex optimizationJim Zhao, Nikita Doikov, Aurélien Lucchi. 811-819 [doi]
• Consistent Validation for Predictive Methods in Spatial SettingsDavid R. Burt, Yunyi Shen, Tamara Broderick. 820-828 [doi]
• Get rid of your constraints and reparametrize: A study in NNLS and implicit biasHung Hsu Chou, Johannes Maly, Claudio Mayrink Verdun, Bernardo Freitas Paulo da Costa, Heudson Mirandola. 829-837 [doi]
• Collaborative non-parametric two-sample testingAlejandro D. de la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos. 838-846 [doi]
• Tamed Langevin sampling under weaker conditionsIosif Lytras, Panayotis Mertikopoulos. 847-855 [doi]
• Entropic Matching for Expectation Propagation of Markov Jump ProcessesYannick Eich, Bastian Alt, Heinz Koeppl. 856-864 [doi]
• Global Group Fairness in Federated Learning via Function TrackingYves Rychener, Daniel Kuhn 0001, Yifan Hu. 865-873 [doi]
• Near-Optimal Sample Complexity in Reward-Free Kernel-based Reinforcement LearningAya Kayal, Sattar Vakili, Laura Toni, Alberto Bernacchia. 874-882 [doi]
• Poisoning Bayesian Inference via Data Deletion and ReplicationMatthieu Carreau, Roi Naveiro, William N. Caballero. 883-891 [doi]
• Near-optimal algorithms for private estimation and sequential testing of collision probabilityRóbert Istvan Busa-Fekete, Umar Syed. 892-900 [doi]
• Fundamental Limits of Perfect Concept ErasureSomnath Basu Roy Chowdhury, Kumar Avinava Dubey, Ahmad Beirami, Rahul Kidambi, Nicholas Monath, Amr Ahmed 0001, Snigdha Chaturvedi. 901-909 [doi]
• Perfect Recovery for Random Geometric Graph Matching with Shallow Graph Neural NetworksSuqi Liu, Morgane Austern. 910-918 [doi]
• Microfoundation inference for strategic predictionDaniele Bracale, Subha Maity, Felipe Maia Polo, Seamus Somerstep, Moulinath Banerjee, Yuekai Sun. 919-927 [doi]
• Heterogeneous Graph Structure Learning through the Lens of Data-generating ProcessesKeyue Jiang, Bohan Tang, Xiaowen Dong 0001, Laura Toni. 928-936 [doi]
• Superiority of Multi-Head Attention: A Theoretical Study in Shallow Transformers in In-Context Linear RegressionYingqian Cui, Jie Ren 0019, Pengfei He, Hui Liu 0031, Jiliang Tang, Yue Xing 0002. 937-945 [doi]
• Balls-and-Bins Sampling for DP-SGDLynn Chua, Badih Ghazi, Charlie Harrison, Pritish Kamath, Ravi Kumar 0001, Ethan Leeman, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang. 946-954 [doi]
• Distance Estimation for High-Dimensional Discrete DistributionsKuldeep S. Meel, Gunjan Kumar, Yash Pote. 955-963 [doi]
• Type Information-Assisted Self-Supervised Knowledge Graph DenoisingJiaqi Sun, Yujia Zheng 0001, Xinshuai Dong, Haoyue Dai, Kun Zhang 0001. 964-972 [doi]
• Learning the Distribution Map in Reverse Causal Performative PredictionDaniele Bracale, Subha Maity, Yuekai Sun, Moulinath Banerjee. 973-981 [doi]
• Optimizing Neural Network Training and Quantization with Rooted Logistic ObjectivesZhu Wang, Praveen Raj Veluswami, Harsh Mishra, Sathya N. Ravi. 982-990 [doi]
• Planning and Learning in Risk-Aware Restless Multi-Arm BanditsNima Akbarzadeh, Yossiri Adulyasak, Erick Delage. 991-999 [doi]
• Pareto Set Identification With Posterior SamplingCyrille Kone, Marc Jourdan, Emilie Kaufmann. 1000-1008 [doi]
• Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein DistancesXuefeng Gao, Lingjiong Zhu. 1009-1017 [doi]
• Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data ManifoldsXingzhi Sun 0003, Danqi Liao, Kincaid MacDonald, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim G. J. Rudner, Smita Krishnaswamy. 1018-1026 [doi]
• Q-function Decomposition with Intervention Semantics for Factored Action SpacesJunkyu Lee 0001, Tian Gao, Elliot Nelson, Miao Liu 0001, Debarun Bhattacharjya, Songtao Lu. 1027-1035 [doi]
• HAR-former: Hybrid Transformer with an Adaptive Time-Frequency Representation Matrix for Long-Term Series ForecastingKenghao Zheng, Zi Long, Shuxin Wang. 1036-1044 [doi]
• Bayesian Decision Theory on Decision Trees: Uncertainty Evaluation and InterpretabilityYuta Nakahara, Shota Saito, Naoki Ichijo, Koki Kazama, Toshiyasu Matsushima. 1045-1053 [doi]
• Hybrid Transfer Reinforcement Learning: Provable Sample Efficiency from Shifted-Dynamics DataChengrui Qu, Laixi Shi, Kishan Panaganti, Pengcheng You, Adam Wierman. 1054-1062 [doi]
• Trustworthy assessment of heterogeneous treatment effect estimator via analysis of relative errorZijun Gao. 1063-1071 [doi]
• Learning-Augmented Algorithms for Online Concave Packing and Convex Covering ProblemsElena Grigorescu, Young-San Lin, Maoyuan Song. 1072-1080 [doi]
• On the Power of Adaptive Weighted Aggregation in Heterogeneous Federated Learning and BeyondDun Zeng, Zenglin Xu, Shiyu Liu, Yu Pan 0005, Qifan Wang 0001, Xiaoying Tang 0002. 1081-1089 [doi]
• Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak LearnersYuxin Wang 0005, Botian Jiang, Yiran Guo, Quan Gan, David Wipf, Xuanjing Huang 0001, Xipeng Qiu. 1090-1098 [doi]
• Locally Optimal Descent for Dynamic Stepsize SchedulingGilad Yehudai, Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain. 1099-1107 [doi]
• Online Student-t Processes with an Overall-local Scale Structure for Modelling Non-stationary DataTaole Sha, Michael Minyi Zhang. 1108-1116 [doi]
• Policy Teaching via Data Poisoning in Learning from Human PreferencesAndi Nika, Jonathan Nöther, Debmalya Mandal, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic. 1117-1125 [doi]
• Model selection for behavioral learning data and applications to contextual banditsJulien Aubert, Louis Köhler, Luc Lehéricy, Giulia Mezzadri, Patricia Reynaud-Bouret. 1126-1134 [doi]
• Distributional Counterfactual Explanations With Optimal TransportLei You 0002, Lele Cao, Mattias Nilsson, Bo Zhao, Lei Lei. 1135-1143 [doi]
• f-PO: Generalizing Preference Optimization with f-divergence MinimizationJiaqi Han, Mingjian Jiang, Yuxuan Song, Stefano Ermon, Minkai Xu. 1144-1152 [doi]
• Variational Inference on the Boolean Hypercube with the Quantum EntropyEliot Beyler, Francis Bach 0001. 1153-1161 [doi]
• Optimal Multi-Objective Best Arm Identification with Fixed ConfidenceZhirui Chen, P. N. Karthik, Yeow Meng Chee, Vincent Y. F. Tan. 1162-1170 [doi]
• Symmetry-Based Structured Matrices for Efficient Approximately Equivariant NetworksAshwin Samudre, Mircea Petrache, Brian Nord, Shubhendu Trivedi. 1171-1179 [doi]
• Evaluating Prediction-based Interventions with Human Decision Makers In MindInioluwa Deborah Raji, Lydia T. Liu. 1180-1188 [doi]
• Bandit Pareto Set Identification in a Multi-Output Linear ModelCyrille Kone, Emilie Kaufmann, Laura Richert. 1189-1197 [doi]
• posteriordb: Testing, Benchmarking and Developing Bayesian Inference AlgorithmsMåns Magnusson, Jakob Torgander, Paul-Christian Bürkner, Lu Zhang, Bob Carpenter, Aki Vehtari. 1198-1206 [doi]
• Efficient Optimization Algorithms for Linear Adversarial TrainingAntônio H. Ribeiro, Thomas B. Schön, Dave Zachariah, Francis Bach 0001. 1207-1215 [doi]
• Learning a Single Index Model from Anisotropic Data with Vanilla Stochastic Gradient DescentGuillaume Braun, Minh Ha Quang, Masaaki Imaizumi. 1216-1224 [doi]
• A primer on linear classification with missing dataAngel David Reyero Lobo, Alexis Ayme, Claire Boyer, Erwan Scornet. 1225-1233 [doi]
• Robust Score MatchingRichard Schwank, Andrew McCormack, Mathias Drton. 1234-1242 [doi]
• On the Relationship Between Robustness and Expressivity of Graph Neural NetworksLorenz Kummer, Wilfried N. Gansterer, Nils Morten Kriege. 1243-1251 [doi]
• Parameter estimation in state space models using particle importance samplingYuxiong Gao, Wentao Li, Rong Chen. 1252-1260 [doi]
• Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable ModelFrancesco Saverio Pezzicoli, Valentina Ros, François P. Landes, Marco Baity-Jesi. 1261-1269 [doi]
• 1 Ball for Communication-Efficient Distributed Mean EstimationNithish Suresh Babu, Ritesh Kumar, Shashank Vatedka. 1270-1278 [doi]
• MING: A Functional Approach to Learning Molecular Generative ModelsVan-Khoa Nguyen, Maciej Falkiewicz, Giangiacomo Mercatali, Alexandros Kalousis. 1279-1287 [doi]
• Sequential Kernelized Stein DiscrepancyDiego Martinez-Taboada, Aaditya Ramdas. 1288-1296 [doi]
• SubSearch: Robust Estimation and Outlier Detection for Stochastic Block Models via Subgraph SearchLeonardo Martins Bianco, Christine Keribin, Zacharie Naulet. 1297-1305 [doi]
• Optimal downsampling for Imbalanced Classification with Generalized Linear ModelsYan Chen, Jose H. Blanchet, Krzysztof Dembczynski, Laura Fee Nern, Aaron E. Flores 0001. 1306-1314 [doi]
• Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous AgentsSafwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines. 1315-1323 [doi]
• 1 Regularization and its Theoretical PropertiesKun Zhao, Jiayi Wang, Yifei Lou. 1324-1332 [doi]
• Representer Theorems for Metric and Preference Learning: Geometric Insights and AlgorithmsPeyman Morteza. 1333-1341 [doi]
• UNHaP: Unmixing Noise from Hawkes ProcessesVirginie Loison, Guillaume Staerman, Thomas Moreau 0001. 1342-1350 [doi]
• Axiomatic Explainer Globalness via Optimal TransportDavin Hill, Joshua T. Bone, Aria Masoomi, Max Torop, Jennifer G. Dy. 1351-1359 [doi]
• Integer Programming Based Methods and Heuristics for Causal Graph LearningSanjeeb Dash, Joao Goncalves, Tian Gao. 1360-1368 [doi]
• The VampPrior Mixture ModelAndrew Stirn, David A. Knowles. 1369-1377 [doi]
• MEDUSA: Medical Data Under Shadow Attacks via Hybrid Model InversionAsfandyar Azhar, Paul Thielen, Curtis P. Langlotz. 1378-1386 [doi]
• Proximal Sampler with Adaptive Step SizeBo Yuan, JiaoJiao Fan, Jiaming Liang, Yongxin Chen. 1387-1395 [doi]
• Rate of Model Collapse in Recursive TrainingAnanda Theertha Suresh, Andrew Thangaraj, Aditya Nanda Kishore Khandavally. 1396-1404 [doi]
• A Shared Low-Rank Adaptation Approach to Personalized RLHFRenpu Liu, Peng Wang 0105, Donghao Li, Cong Shen 0001, Jing Yang 0002. 1405-1413 [doi]
• Differentially private algorithms for linear queries via stochastic convex optimizationGiorgio Micali, Clément Lezane, Annika Betken. 1414-1422 [doi]
• Is Merging Worth It? Securely Evaluating the Information Gain for Causal Dataset AcquisitionJake Fawkes, Lucile Ter-Minassian, Desi R. Ivanova, Uri Shalit, Christopher C. Holmes. 1423-1431 [doi]
• Recursive Learning of Asymptotic Variational ObjectivesAlessandro Mastrototaro, Mathias Müller, Jimmy Olsson. 1432-1440 [doi]
• Improving Stochastic Cubic Newton with MomentumEl Mahdi Chayti, Nikita Doikov, Martin Jaggi. 1441-1449 [doi]
• Adaptive Convergence Rates for Log-Concave Maximum LikelihoodGil Kur, Aditya Guntuboyina. 1450-1458 [doi]
• Learning to Negotiate via Voluntary CommitmentShuhui Zhu, Baoxiang Wang 0001, Sriram Ganapathi Subramanian, Pascal Poupart. 1459-1467 [doi]
• Differentiable Calibration of Inexact Stochastic Simulation Models via Kernel Score MinimizationZiwei Su, Diego Klabjan. 1468-1476 [doi]
• Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update TimeVladimir Braverman, Prathamesh Dharangutte, Shreyas Pai, Vihan Shah, Chen Wang 0027. 1477-1485 [doi]
• On Distributional Discrepancy for Experimental Design with General Assignment ProbabilitiesAnup Rao, Peng Zhang. 1486-1494 [doi]
• Dynamic DBSCAN with Euler Tour SequencesSeiyun Shin, Ilan Shomorony, Peter Macgregor. 1495-1503 [doi]
• Differentially Private Range Queries with Correlated Input PerturbationPrathamesh Dharangutte, Jie Gao 0001, Ruobin Gong, Guanyang Wang. 1504-1512 [doi]
• An Adaptive Method for Weak Supervision with Drifting DataAlessio Mazzetto, Reza Esfandiarpoor, Akash Singirikonda, Eli Upfal, Stephen H. Bach. 1513-1521 [doi]
• On the Inherent Privacy of Zeroth-Order Projected Gradient DescentDevansh Gupta, Meisam Razaviyayn, Vatsal Sharan. 1522-1530 [doi]
• Transformers are Provably Optimal In-context Estimators for Wireless CommunicationsVishnu Teja Kunde, Vicram Rajagopalan, Chandra Shekhara Kaushik Valmeekam, Krishna Narayanan 0001, Jean-François Chamberland, Dileep Kalathil, Srinivas Shakkottai. 1531-1539 [doi]
• Multi-Player Approaches for Dueling BanditsOr Raveh, Junya Honda, Masashi Sugiyama. 1540-1548 [doi]
• Improved dependence on coherence in eigenvector and eigenvalue estimation error boundsHao Yan, Keith Levin. 1549-1557 [doi]
• Provable Benefits of Task-Specific Prompts for In-context LearningXiangyu Chang, Yingcong Li, Muti Kara, Samet Oymak, Amit Roy-Chowdhury 0001. 1558-1566 [doi]
• Neural Point Processes for Pixel-wise RegressionChengzhi Shi, Gözde Özcan, Miquel Sirera Perelló, Yuanyuan Li, Nina Iftikhar Shamsi, Stratis Ioannidis. 1567-1575 [doi]
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• Differentially Private Continual Release of Histograms and Related QueriesMonika Henzinger, A. R. Sricharan, Teresa Anna Steiner. 1990-1998 [doi]
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• Information-Theoretic Causal Discovery in Topological OrderSascha Xu, Sarah Mameche, Jilles Vreeken. 2008-2016 [doi]
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• Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating ProjectionsMarco Miani, Hrittik Roy, Søren Hauberg. 2062-2070 [doi]
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• Robust Gradient Descent for Phase RetrievalAlex Buna, Patrick Rebeschini. 2080-2088 [doi]
• Distribution-Aware Mean Estimation under User-level Local Differential PrivacyCorentin Pla, Maxime Vono, Hugo Richard. 2089-2097 [doi]
• Calibrated Computation-Aware Gaussian ProcessesDisha Hegde, Mohamed Adil, Jon Cockayne. 2098-2106 [doi]
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• Generalization Bounds for Dependent Data using Online-to-Batch ConversionSagnik Chatterjee, Manuj Mukherjee, Alhad Sethi. 2152-2160 [doi]
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• Stochastic Gradient Descent for Bézier Simplex Representation of Pareto Set in Multi-Objective OptimizationYasunari Hikima, Ken Kobayashi, Akinori Tanaka, Akiyoshi Sannai, Naoki Hamada. 3070-3078 [doi]
• HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing RisksXin Liu, Weijia Zhang, Min-Ling Zhang. 3079-3087 [doi]
• Causal discovery in mixed additive noise modelsRuicong Yao, Tim Verdonck, Jakob Raymaekers. 3088-3096 [doi]
• 2: Learning Riemannian Submanifolds from Riemannian DataLeonel Rozo, Miguel González Duque, Noémie Jaquier, Søren Hauberg. 3097-3105 [doi]
• High Dimensional Bayesian Optimization using Lasso Variable SelectionVu Viet Hoang, Hung The Tran, Sunil Gupta 0001, Vu Nguyen 0001. 3106-3114 [doi]
• Differentiable Causal Structure Learning with Identifiability by NOTIMEJeroen Berrevoets, Jakob Raymaekers, Mihaela van der Schaar, Tim Verdonck, Ruicong Yao. 3115-3123 [doi]
• Out-of-distribution robustness for multivariate analysis via causal regularisationHomer Durand, Gherardo Varando, Nathan Mankovich, Gustau Camps-Valls. 3124-3132 [doi]
• Memorization in Attention-only TransformersLéo Dana, Muni Sreenivas Pydi, Yann Chevaleyre. 3133-3141 [doi]
• Multimodal Learning with Uncertainty Quantification based on Discounted Belief FusionGrigor Bezirganyan, Sana Sellami, Laure Berti-Équille, Sébastien Fournier. 3142-3150 [doi]
• Koopman-Equivariant Gaussian ProcessesPetar Bevanda, Max Beier, Alexandre Capone, Stefan Sosnowski, Sandra Hirche, Armin Lederer. 3151-3159 [doi]
• Continuous Structure Constraint Integration for Robust Causal DiscoveryLyuzhou Chen, Taiyu Ban, Derui Lyu, Yijia Sun, Kangtao Hu, Xiangyu Wang 0016, Huanhuan Chen. 3160-3168 [doi]
• Infinite Width Limits of Self Supervised Neural NetworksMaximilian Fleissner, Gautham Govind Anil, Debarghya Ghoshdastidar. 3169-3177 [doi]
• Safety in the Face of Adversity: Achieving Zero Constraint Violation in Online Learning with Slowly Changing ConstraintsBassel Hamoud, Ilnura Usmanova, Kfir Yehuda Levy. 3178-3186 [doi]
• What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much?Rafal Karczewski, Samuel Kaski, Markus Heinonen, Vikas K. Garg 0001. 3187-3195 [doi]
• TRADE: Transfer of Distributions between External Conditions with Normalizing FlowsStefan Wahl, Armand Rousselot, Felix Draxler, Ullrich Köthe. 3196-3204 [doi]
• 2) Convergence with Low-Rank UpdatesSlavomír Hanzely. 3205-3213 [doi]
• Statistical Test for Auto Feature Engineering by Selective InferenceTatsuya Matsukawa, Tomohiro Shiraishi, Shuichi Nishino, Teruyuki Katsuoka, Ichiro Takeuchi. 3214-3222 [doi]
• Differential Privacy in Distributed Learning: Beyond Uniformly Bounded Stochastic GradientsYue Huang, Jiaojiao Zhang, Qing Ling 0001. 3223-3231 [doi]
• Performative Reinforcement Learning with Linear Markov Decision ProcessDebmalya Mandal, Goran Radanovic. 3232-3240 [doi]
• On the Identifiability of Causal AbstractionsXiusi Li, Sékou-Oumar Kaba, Siamak Ravanbakhsh. 3241-3249 [doi]
• Powerful batch conformal prediction for classificationUlysse Gazin, Ruth Heller, Étienne Roquain, Aldo Solari. 3250-3258 [doi]
• Composition and Control with Distilled Energy Diffusion Models and Sequential Monte CarloJames Thornton, Louis Béthune, Ruixiang Zhang, Arwen Bradley, Preetum Nakkiran, Shuangfei Zhai. 3259-3267 [doi]
• Fixed-Budget Change Point Identification in Piecewise Constant BanditsJoseph Lazzaro, Ciara Pike-Burke. 3268-3276 [doi]
• Tensor Network Based Feature Learning ModelAlbert Saiapin, Kim Batselier. 3277-3285 [doi]
• Sample Compression Unleashed: New Generalization Bounds for Real Valued LossesMathieu Bazinet, Valentina Zantedeschi, Pascal Germain. 3286-3294 [doi]
• Global Ground Metric Learning with Applications to scRNA dataDamin Kühn, Michael T. Schaub. 3295-3303 [doi]
• Independent Learning in Performative Markov Potential GamesRilind Sahitaj, Paulius Sasnauskas, Yigit Yalin, Debmalya Mandal, Goran Radanovic. 3304-3312 [doi]
• Parallel Backpropagation for Inverse of a Convolution with Application to Normalizing FlowsSandeep Nagar, Girish Varma. 3313-3321 [doi]
• A Differential Inclusion Approach for Learning Heterogeneous Sparsity in Neuroimaging AnalysisWenjing Han, Yueming Wu, Xinwei Sun 0001, Lingjing Hu, Yizhou Wang 0001. 3322-3330 [doi]
• Narrowing the Gap between Adversarial and Stochastic MDPs via Policy OptimizationDaniil Tiapkin, Evgenii Chzhen, Gilles Stoltz. 3331-3339 [doi]
• SNAP: Sequential Non-Ancestor Pruning for Targeted Causal Effect Estimation With an Unknown GraphMátyás Schubert, Tom Claassen, Sara Magliacane. 3340-3348 [doi]
• Do Regularization Methods for Shortcut Mitigation Work As Intended?Haoyang Hong, Ioanna Papanikolaou, Sonali Parbhoo. 3349-3357 [doi]
• Hyperbolic Prototypical Entailment Cones for Image ClassificationSamuele Fonio, Roberto Esposito, Marco Aldinucci. 3358-3366 [doi]
• Information Transfer Across Clinical Tasks via Adaptive Parameter OptimisationAnshul Thakur, Elena Gal, Soheila Molaei, Xiao Gu 0003, Patrick Schwab, Danielle Belgrave, Kim Branson 0001, David A. Clifton. 3367-3375 [doi]
• Online-to-PAC generalization bounds under graph-mixing dependenciesBaptiste Abélès, Gergely Neu, Eugenio Clerico. 3376-3384 [doi]
• Covariance Selection over NetworksWenfu Xia, Fengpei Li, Ying Sun, Ziping Zhao 0002. 3385-3393 [doi]
• Sparse Causal Effect Estimation using Two-Sample Summary Statistics in the Presence of Unmeasured ConfoundingShimeng Huang, Niklas Pfister, Jack Bowden. 3394-3402 [doi]
• Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural NetworksFelix Jimenez 0002, Matthias Katzfuss. 3403-3411 [doi]
• Separation-Based Distance Measures for Causal GraphsJonas Wahl, Jakob Runge. 3412-3420 [doi]
• Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPsSwetha Ganesh, Washim Uddin Mondal, Vaneet Aggarwal. 3421-3429 [doi]
• FreqMoE: Enhancing Time Series Forecasting through Frequency Decomposition Mixture of ExpertsZiqi Liu 0001. 3430-3438 [doi]
• Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax OptimizationFeihu Huang 0001, Chunyu Xuan, Xinrui Wang 0003, Siqi Zhang, Songcan Chen. 3439-3447 [doi]
• Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-AnalysisRémi Khellaf, Aurélien Bellet, Julie Josse. 3448-3456 [doi]
• Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse GraphsKrzysztof Marcin Choromanski, Isaac Reid, Arijit Sehanobish, Kumar Avinava Dubey. 3457-3465 [doi]
• Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation MatrixCharles Margossian, Lawrence K. Saul. 3466-3474 [doi]
• A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware DemonstrationYingqian Cui, Pengfei He, Xianfeng Tang, Qi He 0002, Chen Luo 0003, Jiliang Tang, Yue Xing 0002. 3475-3483 [doi]
• A graphical global optimization framework for parameter estimation of statistical models with nonconvex regularization functionsDanial Davarnia, Mohammadreza Kiaghadi. 3484-3492 [doi]
• High-Dimensional Differential Parameter Inference in Exponential Family using Time Score MatchingDaniel J. Williams, Leyang Wang, Qizhen Ying, Song Liu 0002, Mladen Kolar. 3493-3501 [doi]
• Large Covariance Matrix Estimation With Nonnegative CorrelationsYixin Yan, Qiao Yang, Ziping Zhao. 3502-3510 [doi]
• TVineSynth: A Truncated C-Vine Copula Generator of Synthetic Tabular Data to Balance Privacy and UtilityElisabeth Griesbauer, Claudia Czado, Arnoldo Frigessi, Ingrid Hobæk Haff. 3511-3519 [doi]
• Fairness Risks for Group-Conditionally Missing DemographicsKaiqi Jiang, Wenzhe Fan, Mao Li, Xinhua Zhang. 3520-3528 [doi]
• Anytime-Valid A/B Testing of Counting ProcessesMichael Lindon, Nathan Kallus. 3529-3537 [doi]
• Diffusion Models under Group TransformationsHaoye Lu, Spencer Szabados, Yaoliang Yu. 3538-3546 [doi]
• Theoretical Convergence Guarantees for Variational AutoencodersSobihan Surendran, Antoine Godichon-Baggioni, Sylvain Le Corff. 3547-3555 [doi]
• Infinite-dimensional Diffusion Bridge Simulation via Operator LearningGefan Yang, Elizabeth Louise Baker, Michael L. Severinsen, Christy Anna Hipsley, Stefan Sommer. 3556-3564 [doi]
• Natural Language Counterfactual Explanations for Graphs Using Large Language ModelsFlavio Giorgi, Cesare Campagnano, Fabrizio Silvestri, Gabriele Tolomei. 3565-3573 [doi]
• Nonparametric estimation of Hawkes processes with RKHSsAnna Bonnet, Maxime Sangnier. 3574-3582 [doi]
• Rethinking Neural-based Matrix Inversion: Why can't, and Where canYuliang Ji, Jian Wu, Yuanzhe Xi. 3583-3591 [doi]
• A Safe Exploration Approach to Constrained Markov Decision ProcessesTingting Ni, Maryam Kamgarpour. 3592-3600 [doi]
• Towards Cost Sensitive Decision MakingYang Li 0012, Junier Oliva. 3601-3609 [doi]
• Weighted Sum of Gaussian Process Latent Variable ModelsJames Odgers, Ruby Sedgwick, Chrysoula Kappatou, Ruth Misener, Sarah Filippi. 3610-3618 [doi]
• Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing RisksJulie Alberge, Vincent Maladière, Olivier Grisel, Judith Abécassis, Gaël Varoquaux. 3619-3627 [doi]
• Density-Dependent Group TestingRahil Morjaria, Saikiran Bulusu, Venkata Gandikota, Sidharth Jaggi. 3628-3636 [doi]
• Offline RL via Feature-Occupancy Gradient AscentGergely Neu, Nneka Okolo. 3637-3645 [doi]
• Gated Recurrent Neural Networks with Weighted Time-Delay FeedbackN. Benjamin Erichson, Soon Hoe Lim, Michael W. Mahoney. 3646-3654 [doi]
• LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual BanditsMasahiro Kato, Shinji Ito. 3655-3663 [doi]
• Theoretically Grounded Pruning of Large Ground Sets for Constrained, Discrete OptimizationAnkur Nath, Alan Kuhnle. 3664-3672 [doi]
• A Novel Convex Gaussian Min Max Theorem for Repeated FeaturesDavid Bosch 0002, Ashkan Panahi. 3673-3681 [doi]
• Unveiling the Role of Randomization in Multiclass Adversarial Classification: Insights from Graph TheoryLucas Gnecco Heredia, Matteo Sammut, Muni Sreenivas Pydi, Rafael Pinot, Benjamin Négrevergne, Yann Chevaleyre. 3682-3690 [doi]
• On the Computational Tractability of the (Many) Shapley ValuesReda Marzouk, Shahaf Bassan, Guy Katz, Colin de la Higuera. 3691-3699 [doi]
• Causal Representation Learning from General Environments under Nonparametric MixingIgnavier Ng, Shaoan Xie, Xinshuai Dong, Peter Spirtes, Kun Zhang 0001. 3700-3708 [doi]
• Conditioning diffusion models by explicit forward-backward bridgingAdrien Corenflos, Zheng Zhao 0004, Thomas B. Schön, Simo Särkkä, Jens Sjölund. 3709-3717 [doi]
• Stochastic Approximation with Unbounded Markovian Noise: A General-Purpose TheoremShaan Ul Haque, Siva Theja Maguluri. 3718-3726 [doi]
• Learning Visual-Semantic Subspace RepresentationsGabriel Moreira, Manuel Marques, João Paulo Costeira, Alexander G. Hauptmann. 3727-3735 [doi]
• Kernel Single Proxy Control for Deterministic ConfoundingLiyuan Xu, Arthur Gretton. 3736-3744 [doi]
• Copula Based Trainable Calibration Error Estimator of Multi-Label Classification with Label InterdependenciesArkapal Panda, Utpal Garain. 3745-3753 [doi]
• Causal Discovery-Driven Change Point Detection in Time SeriesShanyun Gao, Raghavendra Addanki, Tong Yu 0001, Ryan A. Rossi, Murat Kocaoglu. 3754-3762 [doi]
• Scalable Out-of-Distribution Robustness in the Presence of Unobserved ConfoundersParjanya Prajakta Prashant, Seyedeh Baharan Khatami, Bruno Ribeiro 0001, Babak Salimi. 3763-3771 [doi]
• SemlaFlow - Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow MatchingRoss Irwin, Alessandro Tibo, Jon Paul Janet, Simon Olsson. 3772-3780 [doi]
• Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long WayJeongyeol Kwon, Luke Dotson, Yudong Chen 0001, Qiaomin Xie. 3781-3789 [doi]
• Your copula is a classifier in disguise: classification-based copula density estimationDavid Huk, Mark Steel, Ritabrata Dutta. 3790-3798 [doi]
• On Subjective Uncertainty Quantification and Calibration in Natural Language GenerationZiyu Wang, Christopher C. Holmes. 3799-3807 [doi]
• Primal-Dual Spectral Representation for Off-policy EvaluationYang Hu, Tianyi Chen, Na Li 0002, Kai Wang, Bo Dai 0001. 3808-3816 [doi]
• Multi-marginal Schrödinger Bridges with Iterative Reference RefinementYunyi Shen, Renato Berlinghieri, Tamara Broderick. 3817-3825 [doi]
• RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning TasksEduard Tulchinskii, Daria Voronkova, Ilya Trofimov, Evgeny Burnaev, Serguei Barannikov. 3826-3834 [doi]
• Stochastic Compositional Minimax Optimization with Provable Convergence GuaranteesYuyang Deng, Fuli Qiao, Mehrdad Mahdavi. 3835-3843 [doi]
• Tighter Confidence Bounds for Sequential Kernel RegressionHamish Flynn, David Reeb. 3844-3852 [doi]
• Adapting to Online Distribution Shifts in Deep Learning: A Black-Box ApproachDheeraj Baby, Boran Han, Shuai Zhang 0007, Cuixiong Hu, Bernie Wang 0001, Yu-Xiang Wang. 3853-3861 [doi]
• InnerThoughts: Disentangling Representations and Predictions in Large Language ModelsDidier Chételat, Joseph Cotnareanu, Rylee Thompson, Yingxue Zhang 0001, Mark Coates. 3862-3870 [doi]
• Risk-sensitive Bandits: Arm Mixture Optimality and Regret-efficient AlgorithmsMeltem Tatli, Arpan Mukherjee, Prashanth L. A., Karthikeyan Shanmugam, Ali Tajer. 3871-3879 [doi]
• Semiparametric conformal predictionJi-Won Park, KyungHyun Cho. 3880-3888 [doi]
• Learning Geometrically-Informed Lyapunov Functions with Deep Diffeomorphic RBF NetworksSamuel Tesfazgi, Leonhard Sprandl, Sandra Hirche. 3889-3897 [doi]
• Max-Rank: Efficient Multiple Testing for Conformal PredictionAlexander Timans, Christoph Nikolas Straehle, Kaspar Sakmann, Christian A. Naesseth, Eric T. Nalisnick. 3898-3906 [doi]
• Near-Optimal Sample Complexity for Iterated CVaR Reinforcement Learning with a Generative ModelZilong Deng, Simon Khan, Shaofeng Zou. 3907-3915 [doi]
• Steinmetz Neural Networks for Complex-Valued DataShyam Venkatasubramanian, Ali Pezeshki, Vahid Tarokh. 3916-3924 [doi]
• Feasible LearningJuan Ramirez, Ignacio Hounie, Juan Elenter, Jose Gallego-Posada, Meraj Hashemizadeh, Alejandro Ribeiro, Simon Lacoste-Julien. 3925-3933 [doi]
• Task Shift: From Classification to Regression in Overparameterized Linear ModelsTyler Labonte, Kuo-Wei Lai, Vidya Muthukumar. 3934-3942 [doi]
• Fast Convergence of Softmax Policy Mirror AscentReza Asad, Reza Babanezhad Harikandeh, Issam H. Laradji, Nicolas Le Roux, Sharan Vaswani. 3943-3951 [doi]
• Scalable Implicit Graphon LearningAli Azizpour, Nicolas Zilberstein, Santiago Segarra. 3952-3960 [doi]
• Application of Structured State Space Models to High energy physics with locality sensitive hashingCheng Jiang, Sitian Qian. 3961-3969 [doi]
• Analysis of Two-Stage Rollout Designs with Clustering for Causal Inference under Network InterferenceMayleen Cortez-Rodriguez, Matthew Eichhorn, Christina Lee Yu. 3970-3978 [doi]
• The Size of Teachers as a Measure of Data Complexity: PAC-Bayes Excess Risk Bounds and Scaling LawsGintare Karolina Dziugaite, Daniel M. Roy 0001. 3979-3987 [doi]
• DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient FlowsJonathan Geuter, Clément Bonet, Anna Korba, David Alvarez-Melis. 3988-3996 [doi]
• Bridging the Theoretical Gap in Randomized SmoothingBlaise Delattre, Paul Caillon, Quentin Barthélemy, Erwan Fagnou, Alexandre Allauzen. 3997-4005 [doi]
• Distributional Off-policy Evaluation with Bellman Residual MinimizationSungee Hong, Zhengling Qi, Raymond K. W. Wong. 4006-4014 [doi]
• Theory of Agreement-on-the-Line in Linear Models and Gaussian DataChristina Baek, Aditi Raghunathan, J. Zico Kolter. 4015-4023 [doi]
• SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein IdentityPeihao Wang, Zhiwen Fan, Dejia Xu, Dilin Wang, Sreyas Mohan, Forrest N. Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu 0001, Zhangyang Wang, Vikas Chandra. 4024-4032 [doi]
• Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional SettingsHaolin Zou, Arnab Auddy, Kamiar Rahnama Rad, Arian Maleki. 4033-4041 [doi]
• Sampling from the Random Linear Model via Stochastic Localization Up to the AMP ThresholdHan Cui, Zhiyuan Yu, Jingbo Liu. 4042-4050 [doi]
• qttPOTS: Efficient Batch Multiobjective Bayesian Optimization via Pareto Optimal Thompson SamplingAshwin Renganathan, Kade Carlson. 4051-4059 [doi]
• Estimating the Spectral Moments of the Kernel Integral Operator from Finite Sample MatricesChanwoo Chun, SueYeon Chung, Daniel D. Lee. 4060-4068 [doi]
• Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential PrivacyMaryam Aliakbarpour, Syomantak Chaudhuri, Thomas A. Courtade, Alireza Fallah 0001, Michael I. Jordan. 4069-4077 [doi]
• Bayesian Principles Improve Prompt Learning In Vision-Language ModelsMingyu Kim, Jongwoo Ko, Mijung Park. 4078-4086 [doi]
• Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEsEnea Monzio Compagnoni, Rustem Islamov, Frank Norbert Proske, Aurélien Lucchi. 4087-4095 [doi]
• Privacy in Metalearning and Multitask Learning: Modeling and SeparationsMaryam Aliakbarpour, Konstantina Bairaktari, Adam Smith 0006, Marika Swanberg, Jonathan R. Ullman. 4096-4104 [doi]
• Visualizing token importance for black-box language modelsPaulius Rauba, Qiyao Wei, Mihaela van der Schaar. 4105-4113 [doi]
• Tight Analysis of Difference-of-Convex Algorithm (DCA) Improves Convergence Rates for Proximal Gradient DescentTeodor Rotaru, Panagiotis Patrinos, François Glineur. 4114-4122 [doi]
• All or None: Identifiable Linear Properties of Next-Token Predictors in Language ModelingEmanuele Marconato, Sébastien Lachapelle, Sebastian Weichwald, Luigi Gresele. 4123-4131 [doi]
• Learning High-dimensional Gaussians from Censored DataArnab Bhattacharyya 0001, Constantinos Daskalakis, Themis Gouleakis, Yuhao Wang. 4132-4140 [doi]
• Deep Generative Quantile BayesJungeum Kim, Percy S. Zhai, Veronika Rocková. 4141-4149 [doi]
• Double Debiased Machine Learning for Mediation Analysis with Continuous TreatmentsHoussam Zenati, Judith Abécassis, Julie Josse, Bertrand Thirion. 4150-4158 [doi]
• InfoNCE: Identifying the Gap Between Theory and PracticeEvgenia Rusak, Patrik Reizinger, Attila Juhos, Oliver Bringmann 0001, Roland S. Zimmermann, Wieland Brendel. 4159-4167 [doi]
• Achieving $\widetilde{\mathcal{O}}(\sqrt{T})$ Regret in Average-Reward POMDPs with Known Observation ModelsAlessio Russo, Alberto Maria Metelli, Marcello Restelli. 4168-4176 [doi]
• Approximate Equivariance in Reinforcement LearningJung Yeon Park, Sujay Bhatt, Sihan Zeng, Lawson L. S. Wong, Alec Koppel, Sumitra Ganesh, Robin Walters 0001. 4177-4185 [doi]
• The cost of local and global fairness in Federated LearningYuying Duan, Gelei Xu, Yiyu Shi 0001, Michael Lemmon 0001. 4186-4194 [doi]
• Local Stochastic Sensitivity Analysis For Dynamical SystemsNishant Panda, Jehanzeb H. Chaudhry, Natalie Klein, James Carzon, Troy Butler. 4195-4203 [doi]
• Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional ConvergenceBerfin Simsek, Amire Bendjeddou, Daniel Hsu 0001. 4204-4212 [doi]
• Variance-Aware Linear UCB with Deep Representation for Neural Contextual BanditsHa Manh Bui, Enrique Mallada, Anqi Liu. 4213-4221 [doi]
• Robust Estimation in metric spaces: Achieving Exponential Concentration with a Fréchet MedianJakwang Kim, Jiyoung Park, Anirban Bhattacharya. 4222-4230 [doi]
• From Deep Additive Kernel Learning to Last-Layer Bayesian Neural Networks via Induced Prior ApproximationWenyuan Zhao, Haoyuan Chen, Tie Liu 0002, Rui Tuo, Chao Tian 0002. 4231-4239 [doi]
• Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive OrdersChristian Toth, Christian Knoll 0002, Franz Pernkopf, Robert Peharz. 4240-4248 [doi]
• Linear Submodular Maximization with Bandit FeedbackWenjing Chen, Victoria G. Crawford. 4249-4257 [doi]
• Cross-modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal TransportJayoung Ryu, Charlotte Bunne, Luca Pinello, Aviv Regev, Romain Lopez. 4258-4266 [doi]
• Signal Recovery from Random Dot-Product Graphs under Local Differential PrivacySiddharth Vishwanath, Jonathan Hehir. 4267-4275 [doi]
• Synthetic Potential Outcomes and Causal Mixture IdentifiabilityBijan Mazaheri, Chandler Squires, Caroline Uhler. 4276-4284 [doi]
• Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex OptimizationSudeep Salgia, Nikola Pavlovic, Yuejie Chi, Qing Zhao 0001. 4285-4293 [doi]
• Time-varying Gaussian Process Bandits with Unknown PriorJuliusz Ziomek, Masaki Adachi, Michael A. Osborne. 4294-4302 [doi]
• Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment EffectOjash Neopane, Aaditya Ramdas, Aarti Singh. 4303-4311 [doi]
• Behavior-Inspired Neural Networks for Relational InferenceYulong Yang 0003, Bowen Feng, Keqin Wang, Naomi Ehrich Leonard, Adji Bousso Dieng, Christine Allen-Blanchette. 4312-4320 [doi]
• MODL: Multilearner Online Deep LearningAntonios Valkanas, Boris N. Oreshkin, Mark Coates. 4321-4329 [doi]
• Active Feature Acquisition for Personalised Treatment AssignmentJulianna Piskorz, Nicolás Astorga, Jeroen Berrevoets, Mihaela van der Schaar. 4330-4338 [doi]
• ScoreFusion: Fusing Score-based Generative Models via Kullback-Leibler BarycentersHao Liu, Junze Ye, Jose H. Blanchet, Nian Si. 4339-4347 [doi]
• Loss Gradient Gaussian Width based Generalization and Optimization GuaranteesArindam Banerjee 0001, Qiaobo Li, Yingxue Zhou. 4348-4356 [doi]
• On the Power of Multitask Representation Learning with Gradient DescentQiaobo Li, Zixiang Chen, Yihe Deng, Yiwen Kou, Yuan Cao 0006, Quanquan Gu. 4357-4365 [doi]
• Graph Machine Learning based Doubly Robust Estimator for Network Causal EffectsSeyedeh Baharan Khatami, Harsh Parikh, Haowei Chen, Sudeepa Roy, Babak Salimi. 4366-4374 [doi]
• Cross-Modal Imputation and Uncertainty Estimation for Spatial TranscriptomicsXiangyu Guo, Ricardo Henao. 4375-4383 [doi]
• 2AD: Multi-Sensor Multi-System Anomaly Detection through Global Scoring and Calibrated ThresholdingSarah Alnegheimish, Zelin He, Matthew Reimherr, Akash Chandrayan, Abhinav Pradhan, Luca D'Angelo. 4384-4392 [doi]
• Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language ModelsSiyan Zhao, Daniel Israel, Guy Van den Broeck, Aditya Grover. 4393-4401 [doi]
• Stochastic Rounding for LLM Training: Theory and PracticeKaan Ozkara, Tao Yu, Youngsuk Park. 4402-4410 [doi]
• Posterior Mean Matching: Generative Modeling through Online Bayesian InferenceSebastian Salazar, Michal Kucer, Yixin Wang, Emily M. Casleton, David M. Blei. 4411-4419 [doi]
• Offline Multi-task Transfer RL with Representational PenalizationAvinandan Bose, Simon Shaolei Du, Maryam Fazel. 4420-4428 [doi]
• Corruption Robust Offline Reinforcement Learning with Human FeedbackDebmalya Mandal, Andi Nika, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic. 4429-4437 [doi]
• Keeping up with dynamic attackers: Certifying robustness to adaptive online data poisoningAvinandan Bose, Laurent Lessard, Maryam Fazel, Krishnamurthy Dj Dvijotham. 4438-4446 [doi]
• Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient DescentBo Chen 0029, Xiaoyu Li 0001, Yingyu Liang, Zhenmei Shi, Zhao Song 0002. 4447-4455 [doi]
• Online Assortment and Price Optimization Under Contextual Choice ModelsYigit Efe Erginbas, Thomas A. Courtade, Kannan Ramchandran. 4456-4464 [doi]
• SINE: Scalable MPE Inference for Probabilistic Graphical Models using Advanced Neural EmbeddingsShivvrat Arya, Tahrima Rahman, Vibhav Gogate. 4465-4473 [doi]
• Quantifying Knowledge Distillation using Partial Information DecompositionPasan Dissanayake, Faisal Hamman, Barproda Halder, Ilia Sucholutsky, Qiuyi Zhang 0001, Sanghamitra Dutta. 4474-4482 [doi]
• Efficient and Asymptotically Unbiased Constrained Decoding for Large Language ModelsHaotian Ye, Himanshu Jain, Chong You, Ananda Theertha Suresh, Haowei Lin, James Zou 0001, Felix X. Yu. 4483-4491 [doi]
• Cost-Aware Optimal Pairwise Pure ExplorationDi Wu, Chengshuai Shi, Ruida Zhou, Cong Shen 0001. 4492-4500 [doi]
• Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of ExpertsFanqi Yan, Huy Nguyen, Le Quang Dung, Pedram Akbarian, Nhat Ho. 4501-4509 [doi]
• Batch, match, and patch: low-rank approximations for score-based variational inferenceChirag Modi 0002, Diana Cai, Lawrence K. Saul. 4510-4518 [doi]
• Stochastic Weight Sharing for Bayesian Neural NetworksMoule Lin, Shuhao Guan, Weipeng Jing 0001, Goetz Botterweck, Andrea Patane. 4519-4527 [doi]
• Beyond Discretization: Learning the Optimal Solution PathQiran Dong, Paul Grigas, Vishal Gupta. 4528-4536 [doi]
• Faster WIND: Accelerating Iterative Best-of-N Distillation for LLM AlignmentTong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai 0001. 4537-4545 [doi]
• Causal Temporal Regime Structure LearningAbdellah Rahmani, Pascal Frossard. 4546-4554 [doi]
• Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and ApplicationsMatthew Werenski, Brendan Mallery, Shuchin Aeron, James M. Murphy. 4555-4563 [doi]
• General Staircase Mechanisms for Optimal Differential PrivacyAlex Kulesza, Ananda Theertha Suresh, Yuyan Wang. 4564-4572 [doi]
• Understanding the Effect of GCN Convolutions in Regression TasksJuntong Chen, Johannes Schmidt-Hieber, Claire Donnat, Olga Klopp. 4573-4581 [doi]
• Diffusion Models as Constrained Samplers for Optimization with Unknown ConstraintsLingkai Kong, Yuanqi Du, Wenhao Mu, Kirill Neklyudov, Valentin De Bortoli, Dongxia Wu, Haorui Wang, Aaron M. Ferber, Yian Ma, Carla P. Gomes, Chao Zhang 0014. 4582-4590 [doi]
• Learning Pareto manifolds in high dimensions: How can regularization help?Tobias Wegel, Filip Kovacevic, Alexandru Tifrea, Fanny Yang. 4591-4599 [doi]
• Optimal Stochastic Trace Estimation in Generative ModelingXinyang Liu, Hengrong Du, Wei Deng 0002, Ruqi Zhang. 4600-4608 [doi]
• Beyond Size-Based Metrics: Measuring Task-Specific Complexity in Symbolic RegressionKrzysztof Kacprzyk, Mihaela van der Schaar. 4609-4617 [doi]
• Differentially Private Kernelized Contextual BanditsNikola Pavlovic, Sudeep Salgia, Qing Zhao 0001. 4618-4626 [doi]
• Federated Communication-Efficient Multi-Objective OptimizationBaris Askin, Pranay Sharma, Gauri Joshi, Carlee Joe-Wong. 4627-4635 [doi]
• Understanding the Learning Dynamics of LoRA: A Gradient Flow Perspective on Low-Rank Adaptation in Matrix FactorizationZiqing Xu, Hancheng Min, Lachlan Ewen MacDonald, Jinqi Luo, Salma Tarmoun, Enrique Mallada, René Vidal. 4636-4644 [doi]
• Variational Schrödinger Momentum DiffusionKevin Rojas, Yixin Tan, Molei Tao, Yuriy Nevmyvaka, Wei Deng 0002. 4645-4653 [doi]
• Learning to Forget: Bayesian Time Series Forecasting using Recurrent Sparse Spectrum Signature Gaussian ProcessesCsaba Tóth, Masaki Adachi, Michael A. Osborne, Harald Oberhauser. 4654-4662 [doi]
• The Uniformly Rotated Mondrian KernelCalvin Osborne, Eliza O'Reilly. 4663-4671 [doi]
• Adversarial Vulnerabilities in Large Language Models for Time Series ForecastingFuqiang Liu, Sicong Jiang, Luis Miranda-Moreno, Seongjin Choi, Lijun Sun 0001. 4672-4680 [doi]
• Variational Adversarial Training Towards Policies with Improved RobustnessJuncheng Dong, Hao-Lun Hsu, Qitong Gao, Vahid Tarokh, Miroslav Pajic. 4681-4689 [doi]
• Testing Conditional Independence with Deep Neural Network Based Binary Expansion Testing (DeepBET)Yang Yang, Kai Zhang, Ping-Shou Zhong. 4690-4698 [doi]
• Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared RandomnessNikola Pavlovic, Sudeep Salgia, Qing Zhao 0001. 4699-4707 [doi]
• On the Consistent Recovery of Joint Distributions from ConditionalsMahbod Majid, Rattana Pukdee, Vishwajeet Agrawal, Burak Varici, Pradeep Kumar Ravikumar. 4708-4716 [doi]
• Transfer Neyman-Pearson Algorithm for Outlier DetectionMohammadreza M. Kalan, Eitan J. Neugut, Samory Kpotufe. 4717-4725 [doi]
• I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiersRitwik Vashistha, Arya Farahi. 4726-4734 [doi]
• Quantile Additive Trend FilteringZhi Zhang 0012, Kyle Ritscher, Oscar Hernan Madrid Padilla. 4735-4743 [doi]
• A Computation-Efficient Method of Measuring Dataset Quality based on the Coverage of the DatasetBeomjun Kim, Jaehwan Kim, Kangyeon Kim, Sunwoo Kim, Heejin Ahn. 4744-4752 [doi]
• Invariant Link Selector for Spatial-Temporal Out-of-Distribution ProblemKatherine Tieu, Dongqi Fu, Jun Wu 0019, Jingrui He. 4753-4761 [doi]
• Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored DataHongni Wang, Junxi Zhang, Na Li, Linglong Kong, Bei Jiang, Xiaodong Yan. 4762-4770 [doi]
• A Shapley-value Guided Rationale Editor for Rationale LearningZixin Kuang, Meng-Fen Chiang, Wang-Chien Lee. 4771-4779 [doi]
• Bilevel Reinforcement Learning via the Development of Hyper-gradient without Lower-Level ConvexityYan Yang 0012, Bin Gao, Ya-Xiang Yuan. 4780-4788 [doi]
• Regularity in Canonicalized Models: A Theoretical PerspectiveBehrooz Tahmasebi, Stefanie Jegelka. 4789-4797 [doi]
• Graph-based Complexity for Causal Effect by Empirical Plug-inRina Dechter, Anna Raichev, Jin Tian, Alexander Ihler. 4798-4806 [doi]
• Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier mapsRicardo Baptista, Aram-Alexandre Pooladian, Michael Brennan, Youssef Marzouk 0001, Jonathan Niles-Weed. 4807-4815 [doi]
• A Robust Kernel Statistical Test of Invariance: Detecting Subtle AsymmetriesAshkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka, Patrick Jaillet. 4816-4824 [doi]
• Leveraging Frozen Batch Normalization for Co-Training in Source-Free Domain AdaptationXianwen Deng, Yijun Wang, Zhi Xue. 4825-4833 [doi]
• Structure based SAT dataset for analysing GNN generalisationYi Fu, Anthony Tompkins, Yang Song 0001, Maurice Pagnucco. 4834-4842 [doi]
• How Well Can Transformers Emulate In-Context Newton's Method?Angeliki Giannou, Liu Yang 0001, Tianhao Wang 0017, Dimitris Papailiopoulos, Jason D. Lee. 4843-4851 [doi]
• Nonparametric Distributional Regression via Quantile RegressionCheng Peng, Stan Uryasev. 4852-4860 [doi]
• Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer OperatorsNaichang Ke, Ryogo Tanaka, Yoshinobu Kawahara. 4861-4869 [doi]
• Deep Clustering via Probabilistic Ratio-Cut OptimizationAyoub Ghriss, Claire Monteleoni. 4870-4878 [doi]
• Gaussian Mean Testing under TruncationClément Louis Canonne, Themis Gouleakis, Yuhao Wang, Joy Qiping Yang. 4879-4887 [doi]
• Conformal Prediction Under Generalized Covariate Shift with Posterior DriftBaozhen Wang, Xingye Qiao. 4888-4896 [doi]
• Robust Offline Policy Learning with Observational Data from Multiple SourcesAldo Gael Carranza, Susan Athey. 4897-4905 [doi]
• Mixed-Feature Logistic Regression Robust to Distribution ShiftsQingshi Sun, Nathan Justin, Andrés Gómez 0001, Phebe Vayanos. 4906-4914 [doi]
• Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification MetricsJarren Briscoe, Garrett Kepler, Daryl Deford, Assefaw H. Gebremedhin. 4915-4923 [doi]
• Knowledge Graph Completion with Mixed Geometry Tensor FactorizationViacheslav Yusupov, Maxim Rakhuba, Evgeny Frolov. 4924-4932 [doi]
• Unconditionally Calibrated Priors for Beta Mixture Density NetworksAlix Lhéritier, Maurizio Filippone. 4933-4941 [doi]
• Black-Box Uniform Stability for Non-Euclidean Empirical Risk MinimizationSimon Vary, David Martínez-Rubio, Patrick Rebeschini. 4942-4950 [doi]
• Weighted Euclidean Distance Matrices over Mixed Continuous and Categorical Inputs for Gaussian Process ModelsMingyu Pu, Songhao Wang, Haowei Wang, Szu-Hui Ng. 4951-4959 [doi]
• Robust Classification by Coupling Data Mollification with Label SmoothingMarkus Heinonen, Ba-Hien Tran, Michael Kampffmeyer, Maurizio Filippone. 4960-4968 [doi]
• Towards Regulatory-Confirmed Adaptive Clinical Trials: Machine Learning Opportunities and SolutionsOmer Noy Klein, Alihan Hüyük, Ron Shamir, Uri Shalit, Mihaela van der Schaar. 4969-4977 [doi]
• Wasserstein Distributionally Robust Bayesian Optimization with Continuous ContextFrancesco Micheli, Efe C. Balta, Anastasios Tsiamis, John Lygeros. 4978-4986 [doi]
• Noise-Aware Differentially Private Variational InferenceTalal Alrawajfeh, Joonas Jälkö, Antti Honkela. 4987-4995 [doi]
• LITE: Efficiently Estimating Gaussian Probability of MaximalityNicolas Menet, Jonas Hübotter, Parnian Kassraie, Andreas Krause 0001. 4996-5004 [doi]
• Counting Graphlets of Size k under Local Differential PrivacyVorapong Suppakitpaisarn, Donlapark Ponnoprat, Nicha Hirankarn, Quentin Hillebrand. 5005-5013 [doi]
• Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin DynamicsDaniel Paulin, Peter A. Whalley, Neil K. Chada, Benedict J. Leimkuhler. 5014-5022 [doi]
• Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg ExtrapolationPaul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines. 5023-5031 [doi]
• On Local Posterior Structure in Deep EnsemblesMikkel Jordahn, Jonas Vestergaard Jensen, Mikkel N. Schmidt, Michael Riis Andersen. 5032-5040 [doi]
• Personalizing Low-Rank Bayesian Neural Networks Via Federated LearningBoning Zhang, Dongzhu Liu, Osvaldo Simeone, Guanchu Wang, Dimitrios Pezaros, Guangxu Zhu. 5041-5049 [doi]
• Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes TheoryZhi Zhang 0012, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu 0001, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla. 5050-5058 [doi]
• Level Set Teleportation: An Optimization PerspectiveAaron Mishkin, Alberto Bietti, Robert M. Gower. 5059-5067 [doi]
• On the Convergence of Continual Federated Learning Using Incrementally Aggregated GradientsSatish Kumar Keshri, Nazreen Shah, Ranjitha Prasad. 5068-5076 [doi]
• Analyzing Generative Models by Manifold Entropic MetricsDaniel Galperin, Ullrich Köthe. 5077-5085 [doi]
• DPFL: Decentralized Personalized Federated LearningSalma Kharrat, Marco Canini, Samuel Horváth. 5086-5094 [doi]
• Density Ratio-based Proxy Causal Learning Without Density RatiosBariscan Bozkurt, Ben Deaner, Dimitri Meunier, Liyuan Xu, Arthur Gretton. 5095-5103 [doi]
• Certifiably Quantisation-Robust training and inference of Neural NetworksHue Dang, Matthew Wicker, Goetz Botterweck, Andrea Patane. 5104-5112 [doi]
• AlleNoise - large-scale text classification benchmark dataset with real-world label noiseAlicja Raczkowska, Aleksandra Osowska-Kurczab, Jacek Szczerbinski, Kalina Jasinska-Kobus, Klaudia Nazarko. 5113-5121 [doi]
• Strategic Conformal PredictionDaniel Csillag, Cláudio José Struchiner, Guilherme Tegoni Goedert. 5122-5130 [doi]
• Hypernym Bias: Unraveling Deep Classifier Training Dynamics through the Lens of Class HierarchyRoman Malashin, Valeria Yachnaya, Alexandr V. Mullin. 5131-5139 [doi]
• Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game TheoryFabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer, Julia Herbinger. 5140-5148 [doi]
• M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape SchedulingXudong Sun 0002, Nutan Chen, Alexej Gossmann, Yu Xing, Matteo Wohlrapp, Emilio Dorigatti, Carla Feistner, Felix Drost, Daniele Scarcella, Lisa Beer, Carsten Marr. 5149-5157 [doi]
• An Empirical Bernstein Inequality for Dependent Data in Hilbert Spaces and ApplicationsErfan Mirzaei, Andreas Maurer, Vladimir R. Kostic, Massimiliano Pontil. 5158-5166 [doi]
• Training Neural Samplers with Reverse Diffusive KL DivergenceJiajun He 0003, Wenlin Chen, Mingtian Zhang, David Barber, José Miguel Hernández-Lobato. 5167-5175 [doi]
• Every Call is Precious: Global Optimization of Black-Box Functions with Unknown Lipschitz ConstantsFares Fourati, Salma Kharrat, Vaneet Aggarwal, Mohamed-Slim Alouini. 5176-5184 [doi]
• Mean-Field Microcanonical Gradient DescentMarcus Häggbom, Morten Karlsmark, Joakim Andén. 5185-5193 [doi]
• Clustering Context in Off-Policy EvaluationDaniel Guzman-Olivares, Philipp Schmidt 0002, Jacek Golebiowski, Artur Bekasov. 5194-5202 [doi]
• Task-Driven Discrete Representation LearningLong Tung Vuong. 5203-5211 [doi]
• Emergence of Globally Attracting Fixed Points in Deep Neural Networks With Nonlinear ActivationsAmir Joudaki, Thomas Hofmann. 5212-5220 [doi]
• Exposing Privacy Gaps: Membership Inference Attack on Preference Data for LLM AlignmentQizhang Feng, Siva Rajesh Kasa, Santhosh Kumar Kasa, Hyokun Yun, Choon Hui Teo, Sravan Babu Bodapati. 5221-5229 [doi]
• The Strong Product Model for Network Inference without Independence AssumptionsBailey Andrew, David R. Westhead, Luisa Cutillo. 5230-5238 [doi]
• A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous NetworksUday Kiran Reddy Tadipatri, Benjamin David Haeffele, Joshua Agterberg, René Vidal. 5239-5247 [doi]