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Editors: Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li
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Scalable Higher-Order Tensor Product Spline Models
; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1-9
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Fair k-center Clustering with Outliers
Daichi Amagata; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:10-18
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A/B testing under Interference with Partial Network Information
Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:19-27
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Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning
Taeuk Jang, Hongchang Gao, Pengyi Shi, Xiaoqian Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:28-36
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Personalized Federated X-armed Bandit
Wenjie Li, Qifan Song, Jean Honorio; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:37-45
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Non-Neighbors Also Matter to Kriging: A New Contrastive-Prototypical Learning
Zhishuai Li, Yunhao Nie, Ziyue Li, Lei Bai, Yisheng Lv, Rui Zhao; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:46-54
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Boundary-Aware Uncertainty for Feature Attribution Explainers
Davin Hill, Aria Masoomi, Max Torop, Sandesh Ghimire, Jennifer Dy; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:55-63
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Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization
Mathieu Even, Anastasia Koloskova, Laurent Massoulie; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:64-72
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Comparing Comparators in Generalization Bounds
Fredrik Hellström, Benjamin Guedj; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:73-81
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A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization
Mathieu Dagréou, Thomas Moreau, Samuel Vaiter, Pierre Ablin; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:82-90
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Better Batch for Deep Probabilistic Time Series Forecasting
Zhihao Zheng, Seongjin Choi, Lijun Sun; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:91-99
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Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Yifan Hu, Andreas Krause, Ilija Bogunovic; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:100-108
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Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels
Tamim El Ahmad, Luc Brogat-Motte, Pierre Laforgue, Florence d’Alché-Buc; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:109-117
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Ordinal Potential-based Player Rating
Nelson Vadori, Rahul Savani; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:118-126
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Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors
Tim G. J. Rudner, Ya Shi Zhang, Andrew Gordon Wilson, Julia Kempe; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:127-135
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Simple and scalable algorithms for cluster-aware precision medicine
Amanda M. Buch, Conor Liston, Logan Grosenick; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:136-144
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A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport
Tianyi Lin, Marco Cuturi, Michael Jordan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:145-153
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Local Causal Discovery with Linear non-Gaussian Cyclic Models
Haoyue Dai, Ignavier Ng, Yujia Zheng, Zhengqing Gao, Kun Zhang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:154-162
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Density Uncertainty Layers for Reliable Uncertainty Estimation
Yookoon Park, David Blei; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:163-171
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Double InfoGAN for Contrastive Analysis
Florence Carton, Robin Louiset, Pietro Gori; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:172-180
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Is this model reliable for everyone? Testing for strong calibration
Jean Feng, Alexej Gossmann, Romain Pirracchio, Nicholas Petrick, Gene A Pennello, Berkman Sahiner; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:181-189
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An Online Bootstrap for Time Series
Nicolai Palm, Thomas Nagler; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:190-198
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Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective
Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:199-207
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Solving Attention Kernel Regression Problem via Pre-conditioner
Zhao Song, Junze Yin, Lichen Zhang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:208-216
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Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations
Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:217-225
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Identifying Copeland Winners in Dueling Bandits with Indifferences
Viktor Bengs, Björn Haddenhorst, Eyke Hüllermeier; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:226-234
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Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?
Kyurae Kim, Yian Ma, Jacob Gardner; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:235-243
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Fast Dynamic Sampling for Determinantal Point Processes
Zhao Song, Junze Yin, Lichen Zhang, Ruizhe Zhang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:244-252
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Best Arm Identification with Resource Constraints
Zitian Li, Wang Chi Cheung; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:253-261
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Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes
Haoming Yang, Ali Hasan, Yuting Ng, Vahid Tarokh; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:262-270
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HintMiner: Automatic Question Hints Mining From Q&A Web Posts with Language Model via Self-Supervised Learning
Zhenyu Zhang, JiuDong Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:271-279
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A Primal-Dual-Critic Algorithm for Offline Constrained Reinforcement Learning
Kihyuk Hong, Yuhang Li, Ambuj Tewari; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:280-288
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On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function Approximation
Jiawei Huang, Batuhan Yardim, Niao He; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:289-297
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Breaking isometric ties and introducing priors in Gromov-Wasserstein distances
Pinar Demetci, Quang Huy Tran, Ievgen Redko, Ritambhara Singh; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:298-306
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Enhancing In-context Learning via Linear Probe Calibration
Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:307-315
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DNNLasso: Scalable Graph Learning for Matrix-Variate Data
Meixia Lin, Yangjing Zhang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:316-324
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Fast 1-Wasserstein distance approximations using greedy strategies
Guillaume Houry, Han Bao, Han Zhao, Makoto Yamada; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:325-333
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Pure Exploration in Bandits with Linear Constraints
Emil Carlsson, Debabrota Basu, Fredrik Johansson, Devdatt Dubhashi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:334-342
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Emergent specialization from participation dynamics and multi-learner retraining
Sarah Dean, Mihaela Curmei, Lillian Ratliff, Jamie Morgenstern, Maryam Fazel; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:343-351
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Optimal Sparse Survival Trees
Rui Zhang, Rui Xin, Margo Seltzer, Cynthia Rudin; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:352-360
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TenGAN: Pure Transformer Encoders Make an Efficient Discrete GAN for De Novo Molecular Generation
Chen Li, Yoshihiro Yamanishi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:361-369
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Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers
Yuya Yoshikawa, Tomoharu Iwata; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:370-378
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Multi-armed bandits with guaranteed revenue per arm
Dorian Baudry, Nadav Merlis, Mathieu Benjamin Molina, Hugo Richard, Vianney Perchet; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:379-387
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Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication
Hugo Richard, Etienne Boursier, Vianney Perchet; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:388-396
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Error bounds for any regression model using Gaussian processes with gradient information
Rafael Savvides, Hoang Phuc Hau Luu, Kai Puolamäki; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:397-405
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Robust Non-linear Normalization of Heterogeneous Feature Distributions with Adaptive Tanh-Estimators
Felip Guimerà Cuevas, Helmut Schmid; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:406-414
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Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes
Dongxia Wu, Tsuyoshi Ide, Georgios Kollias, Jiri Navratil, Aurelie Lozano, Naoki Abe, Yian Ma, Rose Yu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:415-423
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P-tensors: a General Framework for Higher Order Message Passing in Subgraph Neural Networks
Andrew R. Hands, Tianyi Sun, Risi Kondor; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:424-432
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Faster Convergence with MultiWay Preferences
Aadirupa Saha, Vitaly Feldman, Yishay Mansour, Tomer Koren; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:433-441
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Testing Generated Distributions in GANs to Penalize Mode Collapse
Yanxiang Gong, Zhiwei Xie, Mei Xie, Xin Ma; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:442-450
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The Galerkin method beats Graph-Based Approaches for Spectral Algorithms
Vivien A. Cabannes, Francis Bach; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:451-459
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Online Distribution Learning with Local Privacy Constraints
Jin Sima, Changlong Wu, Olgica Milenkovic, Wojciech Szpankowski; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:460-468
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Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable
Hyeok Kyu Kwon, Minwoo Chae; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:469-477
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Delegating Data Collection in Decentralized Machine Learning
Nivasini Ananthakrishnan, Stephen Bates, Michael Jordan, Nika Haghtalab; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:478-486
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Adaptive Compression in Federated Learning via Side Information
Berivan Isik, Francesco Pase, Deniz Gunduz, Sanmi Koyejo, Tsachy Weissman, Michele Zorzi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:487-495
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Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach
Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:496-504
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Looping in the Human: Collaborative and Explainable Bayesian Optimization
Masaki Adachi, Brady Planden, David Howey, Michael A. Osborne, Sebastian Orbell, Natalia Ares, Krikamol Muandet, Siu Lun Chau; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:505-513
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Efficient Quantum Agnostic Improper Learning of Decision Trees
Sagnik Chatterjee, Tharrmashastha SAPV, Debajyoti Bera; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:514-522
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Meta Learning in Bandits within shared affine Subspaces
Steven Bilaj, Sofien Dhouib, Setareh Maghsudi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:523-531
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VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates
Guillaume Braun, Masashi Sugiyama; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:532-540
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Robust Offline Reinforcement Learning with Heavy-Tailed Rewards
Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:541-549
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The Risks of Recourse in Binary Classification
Hidde Fokkema, Damien Garreau, Tim van Erven; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:550-558
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Prior-dependent analysis of posterior sampling reinforcement learning with function approximation
Yingru Li, Zhiquan Luo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:559-567
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Graph Partitioning with a Move Budget
Mina Dalirrooyfard, Elaheh Fata, Majid Behbahani, Yuriy Nevmyvaka; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:568-576
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On Ranking-based Tests of Independence
Myrto Limnios, Stéphan Clémençon; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:577-585
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Structured Transforms Across Spaces with Cost-Regularized Optimal Transport
Othmane Sebbouh, Marco Cuturi, Gabriel Peyré; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:586-594
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Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias
Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:595-603
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Clustering Items From Adaptively Collected Inconsistent Feedback
Shubham Gupta, Peter W J Staar, Christian de Sainte Marie; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:604-612
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Compression with Exact Error Distribution for Federated Learning
Mahmoud Hegazy, Rémi Leluc, Cheuk Ting Li, Aymeric Dieuleveut; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:613-621
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Deep anytime-valid hypothesis testing
Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:622-630
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Federated Linear Contextual Bandits with Heterogeneous Clients
Ethan Blaser, Chuanhao Li, Hongning Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:631-639
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LEDetection: A Simple Framework for Semi-Supervised Few-Shot Object Detection
Phi Vu Tran; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:640-648
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AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms
Rustem Islamov, Mher Safaryan, Dan Alistarh; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:649-657
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Directional Optimism for Safe Linear Bandits
Spencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:658-666
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Theory-guided Message Passing Neural Network for Probabilistic Inference
Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:667-675
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Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters
Zhenyu Sun, Xiaochun Niu, Ermin Wei; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:676-684
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Mechanics of Next Token Prediction with Self-Attention
Yingcong Li, Yixiao Huang, Muhammed E. Ildiz, Ankit Singh Rawat, Samet Oymak; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:685-693
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Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization
Siqi Zhang, Yifan Hu, Liang Zhang, Niao He; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:694-702
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TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression
Zelin He, Ying Sun, Runze Li; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:703-711
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Fusing Individualized Treatment Rules Using Secondary Outcomes
Daiqi Gao, Yuanjia Wang, Donglin Zeng; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:712-720
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Exploration via linearly perturbed loss minimisation
David Janz, Shuai Liu, Alex Ayoub, Csaba Szepesvári; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:721-729
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Proximal Causal Inference for Synthetic Control with Surrogates
Jizhou Liu, Eric Tchetgen Tchetgen, Carlos Varjão; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:730-738
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Reparameterized Variational Rejection Sampling
Martin Jankowiak, Du Phan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:739-747
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E(3)-Equivariant Mesh Neural Networks
Thuan Anh Trang, Nhat Khang Ngo, Daniel T. Levy, Thieu Ngoc Vo, Siamak Ravanbakhsh, Truong Son Hy; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:748-756
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A General Algorithm for Solving Rank-one Matrix Sensing
Lianke Qin, Zhao Song, Ruizhe Zhang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:757-765
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Oracle-Efficient Pessimism: Offline Policy Optimization In Contextual Bandits
Lequn Wang, Akshay Krishnamurthy, Alex Slivkins; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:766-774
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The Solution Path of SLOPE
Xavier Dupuis, Patrick Tardivel; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:775-783
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Lower-level Duality Based Reformulation and Majorization Minimization Algorithm for Hyperparameter Optimization
He Chen, Haochen Xu, Rujun Jiang, Anthony Man-Cho So; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:784-792
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A Unified Framework for Discovering Discrete Symmetries
Pavan Karjol, Rohan Kashyap, Aditya Gopalan, A. P. Prathosh; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:793-801
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Recovery Guarantees for Distributed-OMP
Chen Amiraz, Robert Krauthgamer, Boaz Nadler; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:802-810
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Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of Outliers
Matteo Vilucchio, Emanuele Troiani, Vittorio Erba, Florent Krzakala; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:811-819
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Riemannian Laplace Approximation with the Fisher Metric
Hanlin Yu, Marcelo Hartmann, Bernardo Williams Moreno Sanchez, Mark Girolami, Arto Klami; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:820-828
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Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support
Tim Reichelt, Luke Ong, Tom Rainforth; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:829-837
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Sharp error bounds for imbalanced classification: how many examples in the minority class?
Anass Aghbalou, Anne Sabourin, François Portier; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:838-846
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Making Better Use of Unlabelled Data in Bayesian Active Learning
Freddie Bickford Smith, Adam Foster, Tom Rainforth; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:847-855
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Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems
Nikita Puchkin, Eduard Gorbunov, Nickolay Kutuzov, Alexander Gasnikov; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:856-864
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Multi-Domain Causal Representation Learning via Weak Distributional Invariances
Kartik Ahuja, Amin Mansouri, Yixin Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:865-873
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Unsupervised Novelty Detection in Pretrained Representation Space with Locally Adapted Likelihood Ratio
Amirhossein Ahmadian, Yifan Ding, Gabriel Eilertsen, Fredrik Lindsten; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:874-882
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Adaptive Quasi-Newton and Anderson Acceleration Framework with Explicit Global (Accelerated) Convergence Rates
Damien Scieur; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:883-891
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BOBA: Byzantine-Robust Federated Learning with Label Skewness
Wenxuan Bao, Jun Wu, Jingrui He; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:892-900
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A White-Box False Positive Adversarial Attack Method on Contrastive Loss Based Offline Handwritten Signature Verification Models
Zhongliang Guo, Weiye Li, Yifei Qian, Ognjen Arandjelovic, Lei Fang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:901-909
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Categorical Generative Model Evaluation via Synthetic Distribution Coarsening
Florence Regol, Mark Coates; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:910-918
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Monitoring machine learning-based risk prediction algorithms in the presence of performativity
Jean Feng, Alexej Gossmann, Gene A Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:919-927
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Learning-Based Algorithms for Graph Searching Problems
Adela F. DePavia, Erasmo Tani, Ali Vakilian; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:928-936
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Autoregressive Bandits
Francesco Bacchiocchi, Gianmarco Genalti, Davide Maran, Marco Mussi, Marcello Restelli, Nicola Gatti, Alberto Maria Metelli; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:937-945
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DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data
Taehyo Kim, Hai Shu, Qiran Jia, Mony de Leon; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:946-954
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Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization
Zhenzhang Ye, Gabriel Peyré, Daniel Cremers, Pierre Ablin; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:955-963
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MINTY: Rule-based models that minimize the need for imputing features with missing values
Lena Stempfle, Fredrik Johansson; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:964-972
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Multi-Dimensional Hyena for Spatial Inductive Bias
Itamar Zimerman, Lior Wolf; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:973-981
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Graph Machine Learning through the Lens of Bilevel Optimization
Amber Yijia Zheng, Tong He, Yixuan Qiu, Minjie Wang, David Wipf; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:982-990
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Robust Sparse Voting
Youssef Allouah, Rachid Guerraoui, Lê-Nguyên Hoang, Oscar Villemaud; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:991-999
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Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity
Siddharth Joshi, Arnav Jain, Ali Payani, Baharan Mirzasoleiman; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1000-1008
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Efficient Low-Dimensional Compression of Overparameterized Models
Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, Qing Qu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1009-1017
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Data-Adaptive Probabilistic Likelihood Approximation for Ordinary Differential Equations
Mohan Wu, Martin Lysy; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1018-1026
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Fairness in Submodular Maximization over a Matroid Constraint
Marwa El Halabi, Jakub Tarnawski, Ashkan Norouzi-Fard, Thuy-Duong Vuong; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1027-1035
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Unified Transfer Learning in High-Dimensional Linear Regression
Shuo Shuo Liu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1036-1044
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Hidden yet quantifiable: A lower bound for confounding strength using randomized trials
Piersilvio De Bartolomeis, Javier Abad Martinez, Konstantin Donhauser, Fanny Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1045-1053
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Towards Achieving Sub-linear Regret and Hard Constraint Violation in Model-free RL
Arnob Ghosh, Xingyu Zhou, Ness Shroff; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1054-1062
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Distributionally Robust Quickest Change Detection using Wasserstein Uncertainty Sets
Liyan Xie, Yuchen Liang, Venugopal V. Veeravalli; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1063-1071
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Quantifying Uncertainty in Natural Language Explanations of Large Language Models
Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1072-1080
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Submodular Minimax Optimization: Finding Effective Sets
Loay Raed Mualem, Ethan R Elenberg, Moran Feldman, Amin Karbasi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1081-1089
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Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability
Rajdeep Haldar, Yue Xing, Qifan Song; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1090-1098
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Information-theoretic Analysis of Bayesian Test Data Sensitivity
Futoshi Futami, Tomoharu Iwata; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1099-1107
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Scalable Algorithms for Individual Preference Stable Clustering
Ron Mosenzon, Ali Vakilian; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1108-1116
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Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles
Fan Yang, Pierre Le Bodic, Michael Kamp, Mario Boley; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1117-1125
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When No-Rejection Learning is Consistent for Regression with Rejection
Xiaocheng Li, Shang Liu, Chunlin Sun, Hanzhao Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1126-1134
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Filter, Rank, and Prune: Learning Linear Cyclic Gaussian Graphical Models
Soheun Yi, Sanghack Lee; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1135-1143
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Robust variance-regularized risk minimization with concomitant scaling
Matthew J. Holland; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1144-1152
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Fast and Adversarial Robust Kernelized SDU Learning
Yajing Fan, wanli shi, Yi Chang, Bin Gu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1153-1161
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Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization
Zhou Zhai, Wanli Shi, Heng Huang, Yi Chang, Bin Gu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1162-1170
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Efficient Graph Laplacian Estimation by Proximal Newton
Yakov Medvedovsky, Eran Treister, Tirza S Routtenberg; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1171-1179
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Adaptive Experiment Design with Synthetic Controls
Alihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1180-1188
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Online non-parametric likelihood-ratio estimation by Pearson-divergence functional minimization
Alejandro D. de la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1189-1197
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Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results
Ainhize Barrainkua, Paula Gordaliza, Jose A. Lozano, Novi Quadrianto; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1198-1206
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Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates
Ahmad Rammal, Kaja Gruntkowska, Nikita Fedin, Eduard Gorbunov, Peter Richtarik; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1207-1215
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Best-of-Both-Worlds Algorithms for Linear Contextual Bandits
Yuko Kuroki, Alberto Rumi, Taira Tsuchiya, Fabio Vitale, Nicolò Cesa-Bianchi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1216-1224
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Fixed-Budget Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit
Shintaro Nakamura, Masashi Sugiyama; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1225-1233
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Scalable Learning of Item Response Theory Models
Susanne Frick, Amer Krivosija, Alexander Munteanu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1234-1242
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Corruption-Robust Offline Two-Player Zero-Sum Markov Games
Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1243-1251
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Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum
Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Yu Inatsu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1252-1260
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Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models
Frederiek Wesel, Kim Batselier; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1261-1269
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Fair Soft Clustering
Rune D. Kjærsgaard, Pekka Parviainen, Saket Saurabh, Madhumita Kundu, Line Clemmensen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1270-1278
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Simulation-Free Schrödinger Bridges via Score and Flow Matching
Alexander Y. Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1279-1287
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Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
Alexia Jolicoeur-Martineau, Kilian Fatras, Tal Kachman; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1288-1296
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Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels
Raphaël Carpintero Perez, Sébastien Da Veiga, Josselin Garnier, Brian Staber; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1297-1305
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Intrinsic Gaussian Vector Fields on Manifolds
Daniel Robert-Nicoud, Andreas Krause, Viacheslav Borovitskiy; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1306-1314
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A Unifying Variational Framework for Gaussian Process Motion Planning
Lucas C. Cosier, Rares Iordan, Sicelukwanda N. T. Zwane, Giovanni Franzese, James T. Wilson, Marc Deisenroth, Alexander Terenin, Yasemin Bekiroglu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1315-1323
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MMD-based Variable Importance for Distributional Random Forest
Clément Bénard, Jeffrey Näf, Julie Josse; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1324-1332
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Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning
Jörn Tebbe, Christoph Zimmer, Ansgar Steland, Markus Lange-Hegermann, Fabian Mies; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1333-1341
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Federated Learning For Heterogeneous Electronic Health Records Utilising Augmented Temporal Graph Attention Networks
Soheila Molaei, Anshul Thakur, Ghazaleh Niknam, Andrew Soltan, Hadi Zare, David A Clifton; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1342-1350
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Adaptive Discretization for Event PredicTion (ADEPT)
Jimmy Hickey, Ricardo Henao, Daniel Wojdyla, Michael Pencina, Matthew Engelhard; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1351-1359
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Generalization Bounds for Label Noise Stochastic Gradient Descent
Jung Eun Huh, Patrick Rebeschini; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1360-1368
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Adaptive Parametric Prototype Learning for Cross-Domain Few-Shot Classification
Marzi Heidari, Abdullah Alchihabi, Qing En, Yuhong Guo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1369-1377
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Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions
Zulqarnain Q. Khan, Davin Hill, Aria Masoomi, Joshua T. Bone, Jennifer Dy; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1378-1386
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Importance Matching Lemma for Lossy Compression with Side Information
Buu Phan, Ashish Khisti, Christos Louizos; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1387-1395
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Certified private data release for sparse Lipschitz functions
Konstantin Donhauser, Johan Lokna, Amartya Sanyal, March Boedihardjo, Robert Hönig, Fanny Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1396-1404
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Sequence Length Independent Norm-Based Generalization Bounds for Transformers
Jacob Trauger, Ambuj Tewari; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1405-1413
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Subsampling Error in Stochastic Gradient Langevin Diffusions
Kexin Jin, Chenguang Liu, Jonas Latz; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1414-1422
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Analysis of Privacy Leakage in Federated Large Language Models
Minh Vu, Truc Nguyen, Tre’ Jeter, My T. Thai; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1423-1431
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Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems
Chendi Qian, Didier Chételat, Christopher Morris; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1432-1440
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Cross-model Mutual Learning for Exemplar-based Medical Image Segmentation
Qing En, Yuhong Guo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1441-1449
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Online Calibrated and Conformal Prediction Improves Bayesian Optimization
Shachi Deshpande, Charles Marx, Volodymyr Kuleshov; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1450-1458
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Offline Policy Evaluation and Optimization Under Confounding
Chinmaya Kausik, Yangyi Lu, Kevin Tan, Maggie Makar, Yixin Wang, Ambuj Tewari; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1459-1467
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Confident Feature Ranking
Bitya Neuhof, Yuval Benjamini; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1468-1476
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Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications
Jie Hu, Vishwaraj Doshi, Do Young Eun; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1477-1485
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Taming False Positives in Out-of-Distribution Detection with Human Feedback
Harit Vishwakarma, Heguang Lin, Ramya Korlakai Vinayak; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1486-1494
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On the Privacy of Selection Mechanisms with Gaussian Noise
Jonathan Lebensold, Doina Precup, Borja Balle; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1495-1503
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Transductive conformal inference with adaptive scores
Ulysse Gazin, Gilles Blanchard, Etienne Roquain; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1504-1512
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Learning Latent Partial Matchings with Gumbel-IPF Networks
Hedda Cohen Indelman, Tamir Hazan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1513-1521
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On Counterfactual Metrics for Social Welfare: Incentives, Ranking, and Information Asymmetry
Serena Wang, Stephen Bates, P Aronow, Michael Jordan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1522-1530
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Data-Driven Online Model Selection With Regret Guarantees
Chris Dann, Claudio Gentile, Aldo Pacchiano; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1531-1539
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Integrating Uncertainty Awareness into Conformalized Quantile Regression
Raphael Rossellini, Rina Foygel Barber, Rebecca Willett; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1540-1548
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On the Expected Size of Conformal Prediction Sets
Guneet S. Dhillon, George Deligiannidis, Tom Rainforth; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1549-1557
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Estimation of partially known Gaussian graphical models with score-based structural priors
Martín Sevilla, Antonio G. Marques, Santiago Segarra; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1558-1566
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Model-Based Best Arm Identification for Decreasing Bandits
Sho Takemori, Yuhei Umeda, Aditya Gopalan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1567-1575
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Thompson Sampling Itself is Differentially Private
Tingting Ou, Rachel Cummings, Marco Avella Medina; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1576-1584
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A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity
Zhihan Xiong, Romain Camilleri, Maryam Fazel, Lalit Jain, Kevin Jamieson; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1585-1593
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Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes
Jinwon Sohn, Qifan Song, Guang Lin; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1594-1602
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Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses
Ziye Ma, Ying Chen, Javad Lavaei, Somayeh Sojoudi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1603-1611
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FedFisher: Leveraging Fisher Information for One-Shot Federated Learning
Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1612-1620
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Causal Discovery under Off-Target Interventions
Davin Choo, Kirankumar Shiragur, Caroline Uhler; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1621-1629
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Feasible $Q$-Learning for Average Reward Reinforcement Learning
Ying Jin, Ramki Gummadi, Zhengyuan Zhou, Jose Blanchet; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1630-1638
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Joint control variate for faster black-box variational inference
Xi Wang, Tomas Geffner, Justin Domke; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1639-1647
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Adaptivity of Diffusion Models to Manifold Structures
Rong Tang, Yun Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1648-1656
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Conformalized Deep Splines for Optimal and Efficient Prediction Sets
Nathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani, Gabriele Scalia; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1657-1665
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Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex
Yasushi Esaki, Akihiro Nakamura, Keisuke Kawano, Ryoko Tokuhisa, Takuro Kutsuna; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1666-1674
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Smoothness-Adaptive Dynamic Pricing with Nonparametric Demand Learning
Zeqi Ye, Hansheng Jiang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1675-1683
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Optimal Exploration is no harder than Thompson Sampling
Zhaoqi Li, Kevin Jamieson, Lalit Jain; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1684-1692
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Sample Complexity Characterization for Linear Contextual MDPs
Junze Deng, Yuan Cheng, Shaofeng Zou, Yingbin Liang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1693-1701
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Sample-Efficient Personalization: Modeling User Parameters as Low Rank Plus Sparse Components
Soumyabrata Pal, Prateek Varshney, Gagan Madan, Prateek Jain, Abhradeep Thakurta, Gaurav Aggarwal, Pradeep Shenoy, Gaurav Srivastava; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1702-1710
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Queuing dynamics of asynchronous Federated Learning
Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1711-1719
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Learning Populations of Preferences via Pairwise Comparison Queries
Gokcan Tatli, Yi Chen, Ramya Korlakai Vinayak; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1720-1728
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A Neural Architecture Predictor based on GNN-Enhanced Transformer
Xunzhi Xiang, Kun Jing, Jungang Xu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1729-1737
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Efficient Neural Architecture Design via Capturing Architecture-Performance Joint Distribution
Yue Liu, Ziyi Yu, Zitu Liu, Wenjie Tian; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1738-1746
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Analysis of Using Sigmoid Loss for Contrastive Learning
Chungpa Lee, Joonhwan Chang, Jy-yong Sohn; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1747-1755
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Robust Data Clustering with Outliers via Transformed Tensor Low-Rank Representation
Tong Wu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1756-1764
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Robust SVD Made Easy: A fast and reliable algorithm for large-scale data analysis
Sangil Han, Sungkyu Jung, Kyoowon Kim; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1765-1773
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Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures
Hao Liang, Zhiquan Luo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1774-1782
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Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean
Anton Frederik Thielmann, René-Marcel Kruse, Thomas Kneib, Benjamin Säfken; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1783-1791
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On The Temporal Domain of Differential Equation Inspired Graph Neural Networks
Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane B Schönlieb; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1792-1800
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Diagonalisation SGD: Fast & Convergent SGD for Non-Differentiable Models via Reparameterisation and Smoothing
Dominik Wagner, Basim Khajwal, Luke Ong; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1801-1809
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Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting
Louis Sharrock, Daniel Dodd, Christopher Nemeth; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1810-1818
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Bayesian Semi-structured Subspace Inference
Daniel Dold, David Ruegamer, Beate Sick, Oliver Dürr; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1819-1827
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CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference
Vo Nguyen Le Duy, Hsuan-Tien Lin, Ichiro Takeuchi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1828-1836
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Provable local learning rule by expert aggregation for a Hawkes network
Sophie Jaffard, Samuel Vaiter, Alexandre Muzy, Patricia Reynaud-Bouret; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1837-1845
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Multitask Online Learning: Listen to the Neighborhood Buzz
Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1846-1854
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Structural perspective on constraint-based learning of Markov networks
Tuukka Korhonen, Fedor Fomin, Pekka Parviainen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1855-1863
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DAGnosis: Localized Identification of Data Inconsistencies using Structures
Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1864-1872
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Bures-Wasserstein Means of Graphs
Isabel Haasler, Pascal Frossard; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1873-1881
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Time to Cite: Modeling Citation Networks using the Dynamic Impact Single-Event Embedding Model
Nikolaos Nakis, Abdulkadir Celikkanat, Louis Boucherie, Sune Lehmann, Morten Mørup; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1882-1890
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Extended Deep Adaptive Input Normalization for Preprocessing Time Series Data for Neural Networks
Marcus A. K. September, Francesco Sanna Passino, Leonie Goldmann, Anton Hinel; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1891-1899
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Restricted Isometry Property of Rank-One Measurements with Random Unit-Modulus Vectors
Wei Zhang, Zhenni Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1900-1908
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Variational Gaussian Process Diffusion Processes
Prakhar Verma, Vincent Adam, Arno Solin; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1909-1917
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Positivity-free Policy Learning with Observational Data
Pan Zhao, Antoine Chambaz, Julie Josse, Shu Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1918-1926
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Causal Modeling with Stationary Diffusions
Lars Lorch, Andreas Krause, Bernhard Schölkopf; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1927-1935
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Learning Dynamics in Linear VAE: Posterior Collapse Threshold, Superfluous Latent Space Pitfalls, and Speedup with KL Annealing
Yuma Ichikawa, Koji Hukushima; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1936-1944
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A 4-Approximation Algorithm for Min Max Correlation Clustering
Holger S. G. Heidrich, Jannik Irmai, Bjoern Andres; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1945-1953
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Ethics in Action: Training Reinforcement Learning Agents for Moral Decision-making In Text-based Adventure Games
Weichen Li, Rati Devidze, Waleed Mustafa, Sophie Fellenz; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1954-1962
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Interpretability Guarantees with Merlin-Arthur Classifiers
Stephan Wäldchen, Kartikey Sharma, Berkant Turan, Max Zimmer, Sebastian Pokutta; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1963-1971
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Classifier Calibration with ROC-Regularized Isotonic Regression
Eugène Berta, Francis Bach, Michael Jordan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1972-1980
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Scalable Meta-Learning with Gaussian Processes
Petru Tighineanu, Lukas Grossberger, Paul Baireuther, Kathrin Skubch, Stefan Falkner, Julia Vinogradska, Felix Berkenkamp; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1981-1989
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An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization
Lesi Chen, Haishan Ye, Luo Luo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1990-1998
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Vector Quantile Regression on Manifolds
Marco Pegoraro, Sanketh Vedula, Aviv A Rosenberg, Irene Tallini, Emanuele Rodola, Alex Bronstein; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1999-2007
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Near-Optimal Convex Simple Bilevel Optimization with a Bisection Method
Jiulin Wang, Xu Shi, Rujun Jiang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2008-2016
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Tackling the XAI Disagreement Problem with Regional Explanations
Gabriel Laberge, Yann Batiste Pequignot, Mario Marchand, Foutse Khomh; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2017-2025
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Training Implicit Generative Models via an Invariant Statistical Loss
José Manuel de Frutos, Pablo Olmos, Manuel Alberto Vazquez Lopez, Joaquín Míguez; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2026-2034
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RL in Markov Games with Independent Function Approximation: Improved Sample Complexity Bound under the Local Access Model
Junyi Fan, Yuxuan Han, Jialin Zeng, Jian-Feng Cai, Yang Wang, Yang Xiang, Jiheng Zhang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2035-2043
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Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games
Jing Dong, Baoxiang Wang, Yaoliang Yu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2044-2052
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GmGM: a fast multi-axis Gaussian graphical model
Ethan B. Andrew, David Westhead, Luisa Cutillo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2053-2061
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On Convergence in Wasserstein Distance and f-divergence Minimization Problems
Cheuk Ting Li, Jingwei Zhang, Farzan Farnia; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2062-2070
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Sparse and Faithful Explanations Without Sparse Models
Yiyang Sun, Zhi Chen, Vittorio Orlandi, Tong Wang, Cynthia Rudin; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2071-2079
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Extragradient Type Methods for Riemannian Variational Inequality Problems
Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D Abernethy, Molei Tao; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2080-2088
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Learning Sparse Codes with Entropy-Based ELBOs
Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2089-2097
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Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed Responses
Shiliang Zuo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2098-2106
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Robust Approximate Sampling via Stochastic Gradient Barker Dynamics
Lorenzo Mauri, Giacomo Zanella; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2107-2115
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Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint
Haoyue Tang, Tian Xie, Aosong Feng, Hanyu Wang, Chenyang Zhang, Yang Bai; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2116-2124
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Enhancing Distributional Stability among Sub-populations
Jiashuo Liu, Jiayun Wu, Jie Peng, Xiaoyu Wu, Yang Zheng, Bo Li, Peng Cui; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2125-2133
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Safe and Interpretable Estimation of Optimal Treatment Regimes
Harsh Parikh, Quinn M Lanners, Zade Akras, Sahar Zafar, M Brandon Westover, Cynthia Rudin, Alexander Volfovsky; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2134-2142
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Probabilistic Integral Circuits
Gennaro Gala, Cassio de Campos, Robert Peharz, Antonio Vergari, Erik Quaeghebeur; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2143-2151
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Learning Extensive-Form Perfect Equilibria in Two-Player Zero-Sum Sequential Games
Martino Bernasconi, Alberto Marchesi, Francesco Trovò; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2152-2160
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Understanding Progressive Training Through the Framework of Randomized Coordinate Descent
Rafał Szlendak, Elnur Gasanov, Peter Richtarik; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2161-2169
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Multiclass Learning from Noisy Labels for Non-decomposable Performance Measures
Mingyuan Zhang, Shivani Agarwal; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2170-2178
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On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers
Cai Zhou, Rose Yu, Yusu Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2179-2187
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Quantifying intrinsic causal contributions via structure preserving interventions
Dominik Janzing, Patrick Blöbaum, Atalanti A Mastakouri, Philipp M Faller, Lenon Minorics, Kailash Budhathoki; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2188-2196
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Free-form Flows: Make Any Architecture a Normalizing Flow
Felix Draxler, Peter Sorrenson, Lea Zimmermann, Armand Rousselot, Ullrich Köthe; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2197-2205
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Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent
Bianca M. Moreno, Margaux Bregere, Pierre Gaillard, Nadia Oudjane; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2206-2214
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Online learning in bandits with predicted context
Yongyi Guo, Ziping Xu, Susan Murphy; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2215-2223
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Optimising Distributions with Natural Gradient Surrogates
Jonathan So, Richard E. Turner; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2224-2232
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Monotone Operator Theory-Inspired Message Passing for Learning Long-Range Interaction on Graphs
Justin M. Baker, Qingsong Wang, Martin Berzins, Thomas Strohmer, Bao Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2233-2241
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Agnostic Multi-Robust Learning using ERM
Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin M Stangl; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2242-2250
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GRAWA: Gradient-based Weighted Averaging for Distributed Training of Deep Learning Models
Tolga Dimlioglu, Anna Choromanska; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2251-2259
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Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent
Pratik Patil, Yuchen Wu, Ryan Tibshirani; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2260-2268
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Imposing Fairness Constraints in Synthetic Data Generation
Mahed Abroshan, Andrew Elliott, Mohammad Mahdi Khalili; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2269-2277
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Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers
Krzysztof Choromanski, Shanda Li, Valerii Likhosherstov, Kumar Avinava Dubey, Shengjie Luo, Di He, Yiming Yang, Tamas Sarlos, Thomas Weingarten, Adrian Weller; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2278-2286
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Backward Filtering Forward Deciding in Linear Non-Gaussian State Space Models
Yun-Peng Li, Hans-Andrea Loeliger; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2287-2295
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MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization
Nguyen Hoang Khoi Do, Tanmoy Chowdhury, Chen Ling, Liang Zhao, My T. Thai; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2296-2304
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A Doubly Robust Approach to Sparse Reinforcement Learning
Wonyoung Kim, Garud Iyengar, Assaf Zeevi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2305-2313
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General Identifiability and Achievability for Causal Representation Learning
Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2314-2322
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Sum-max Submodular Bandits
Stephen U. Pasteris, Alberto Rumi, Fabio Vitale, Nicolò Cesa-Bianchi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2323-2331
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Stochastic Approximation with Biased MCMC for Expectation Maximization
Samuel Gruffaz, Kyurae Kim, Alain Durmus, Jacob Gardner; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2332-2340
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EM for Mixture of Linear Regression with Clustered Data
Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman Ozdaglar; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2341-2349
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Analysis of Kernel Mirror Prox for Measure Optimization
Pavel Dvurechensky, Jia-Jie Zhu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2350-2358
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Implicit Regularization in Deep Tucker Factorization: Low-Rankness via Structured Sparsity
Kais Hariz, Hachem Kadri, Stéphane Ayache, Maher Moakher, Thierry Artières; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2359-2367
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Simulating weighted automata over sequences and trees with transformers
Michael Rizvi-Martel, Maude Lizaire, Clara Lacroce, Guillaume Rabusseau; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2368-2376
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Approximate Leave-one-out Cross Validation for Regression with $\ell_1$ Regularizers
Arnab Auddy, Haolin Zou, Kamiar Rahnamarad, Arian Maleki; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2377-2385
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Learning Safety Constraints from Demonstrations with Unknown Rewards
David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2386-2394
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Online Learning in Contextual Second-Price Pay-Per-Click Auctions
Mengxiao Zhang, Haipeng Luo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2395-2403
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Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
Miguel Fuentes, Brett C. Mullins, Ryan McKenna, Gerome Miklau, Daniel Sheldon; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2404-2412
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Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels
Da Long, Wei Xing, Aditi Krishnapriyan, Robert Kirby, Shandian Zhe, Michael W. Mahoney; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2413-2421
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An Impossibility Theorem for Node Embedding
T. Mitchell Roddenberry, Yu Zhu, Santiago Segarra; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2422-2430
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Mixed variational flows for discrete variables
Gian C. Diluvi, Benjamin Bloem-Reddy, Trevor Campbell; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2431-2439
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Multi-Resolution Active Learning of Fourier Neural Operators
Shibo Li, Xin Yu, Wei Xing, Robert Kirby, Akil Narayan, Shandian Zhe; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2440-2448
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Functional Graphical Models: Structure Enables Offline Data-Driven Optimization
Kuba Grudzien, Masatoshi Uehara, Sergey Levine, Pieter Abbeel; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2449-2457
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Federated Experiment Design under Distributed Differential Privacy
Wei-Ning Chen, Graham Cormode, Akash Bharadwaj, Peter Romov, Ayfer Ozgur; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2458-2466
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Optimal Zero-Shot Detector for Multi-Armed Attacks
Federica Granese, Marco Romanelli, Pablo Piantanida; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2467-2475
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Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective
Sanath Kumar Krishnamurthy, Adrienne M Propp, Susan Athey; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2476-2484
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Conformal Contextual Robust Optimization
Yash P. Patel, Sahana Rayan, Ambuj Tewari; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2485-2493
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Learning Adaptive Kernels for Statistical Independence Tests
Yixin Ren, Yewei Xia, Hao Zhang, Jihong Guan, Shuigeng Zhou; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2494-2502
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Lexicographic Optimization: Algorithms and Stability
Jacob A. Abernethy, Robert Schapire, Umar Syed; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2503-2511
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Can Probabilistic Feedback Drive User Impacts in Online Platforms?
Jessica Dai, Bailey Flanigan, Nika Haghtalab, Meena Jagadeesan, Chara Podimata; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2512-2520
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Learning Cartesian Product Graphs with Laplacian Constraints
Changhao Shi, Gal Mishne; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2521-2529
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Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow
Rentian Yao, Linjun Huang, Yun Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2530-2538
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Bayesian Online Learning for Consensus Prediction
Samuel Showalter, Alex J Boyd, Padhraic Smyth, Mark Steyvers; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2539-2547
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Bandit Pareto Set Identification: the Fixed Budget Setting
Cyrille Kone, Emilie Kaufmann, Laura Richert; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2548-2556
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Efficient Data Shapley for Weighted Nearest Neighbor Algorithms
Jiachen T. Wang, Prateek Mittal, Ruoxi Jia; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2557-2565
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Surrogate Bayesian Networks for Approximating Evolutionary Games
Vincent Hsiao, Dana S Nau, Bobak Pezeshki, Rina Dechter; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2566-2574
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BlockBoost: Scalable and Efficient Blocking through Boosting
Thiago Ramos, Rodrigo Loro Schuller, Alex Akira Okuno, Lucas Nissenbaum, Roberto I Oliveira, Paulo Orenstein; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2575-2583
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Continual Domain Adversarial Adaptation via Double-Head Discriminators
Yan Shen, Zhanghexuan Ji, Chunwei Ma, Mingchen Gao; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2584-2592
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Maximum entropy GFlowNets with soft Q-learning
Sobhan Mohammadpour, Emmanuel Bengio, Emma Frejinger, Pierre-Luc Bacon; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2593-2601
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Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits
Arnab Maiti, Ross Boczar, Kevin Jamieson, Lillian Ratliff; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2602-2610
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Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo
Haoyang Zheng, Wei Deng, Christian Moya, Guang Lin; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2611-2619
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Large-Scale Gaussian Processes via Alternating Projection
Kaiwen Wu, Jonathan Wenger, Haydn T Jones, Geoff Pleiss, Jacob Gardner; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2620-2628
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Achieving Group Distributional Robustness and Minimax Group Fairness with Interpolating Classifiers
Natalia L. Martinez, Martin A. Bertran, Guillermo Sapiro; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2629-2637
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Graph fission and cross-validation
James Leiner, Aaditya Ramdas; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2638-2646
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Graph Pruning for Enumeration of Minimal Unsatisfiable Subsets
Panagiotis Lymperopoulos, Liping Liu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2647-2655
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Nonparametric Automatic Differentiation Variational Inference with Spline Approximation
Yuda Shao, Shan N Yu, Tianshu Feng; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2656-2664
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Strategic Usage in a Multi-Learner Setting
Eliot Shekhtman, Sarah Dean; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2665-2673
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On Parameter Estimation in Deviated Gaussian Mixture of Experts
Huy Nguyen, Khai Nguyen, Nhat Ho; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2674-2682
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Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts
Huy Nguyen, TrungTin Nguyen, Khai Nguyen, Nhat Ho; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2683-2691
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PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model
Abhinav Chakraborty, Anirban Chatterjee, Abhinandan Dalal; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2692-2700
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Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression
Sijin Chen, Zhize Li, Yuejie Chi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2701-2709
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From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach
Tuan Nguyen, Hirotada Honda, Takashi Sano, Vinh Nguyen, Shugo Nakamura, Tan Minh Nguyen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2710-2718
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Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation
Zhishuai Liu, Pan Xu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2719-2727
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Invariant Aggregator for Defending against Federated Backdoor Attacks
Xiaoyang Wang, Dimitrios Dimitriadis, Sanmi Koyejo, Shruti Tople; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2728-2736
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Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis
Zihao Li, Xiang Ji, Minshuo Chen, Mengdi Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2737-2745
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Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling
Arman Adibi, Nicolò Dal Fabbro, Luca Schenato, Sanjeev Kulkarni, H. Vincent Poor, George J. Pappas, Hamed Hassani, Aritra Mitra; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2746-2754
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Privacy-Preserving Decentralized Actor-Critic for Cooperative Multi-Agent Reinforcement Learning
Maheed H. Ahmed, Mahsa Ghasemi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2755-2763
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On the Model-Misspecification in Reinforcement Learning
Yunfan Li, Lin Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2764-2772
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Any-dimensional equivariant neural networks
Eitan Levin, Mateo Diaz; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2773-2781
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Conditional Adjustment in a Markov Equivalence Class
Sara LaPlante, Emilija Perkovic; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2782-2790
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Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models
Shivvrat Arya, Tahrima Rahman, Vibhav Gogate; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2791-2799
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Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression
Zhaoyang Shi, Krishna Balasubramanian, Wolfgang Polonik; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2800-2808
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Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients
Chris J. Cundy, Rishi Desai, Stefano Ermon; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2809-2817
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Deep Dependency Networks and Advanced Inference Schemes for Multi-Label Classification
Shivvrat Arya, Yu Xiang, Vibhav Gogate; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2818-2826
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Near-optimal Per-Action Regret Bounds for Sleeping Bandits
Quan M. Nguyen, Nishant Mehta; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2827-2835
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Electronic Medical Records Assisted Digital Clinical Trial Design
Xinrui Ruan, Jingshen Wang, Yingfei Wang, Waverly Wei; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2836-2844
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Multivariate Time Series Forecasting By Graph Attention Networks With Theoretical Guarantees
Zhi Zhang, Weijian Li, Han Liu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2845-2853
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Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods
Davoud Ataee Tarzanagh, Parvin Nazari, Bojian Hou, Li Shen, Laura Balzano; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2854-2862
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End-to-end Feature Selection Approach for Learning Skinny Trees
Shibal Ibrahim, Kayhan Behdin, Rahul Mazumder; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2863-2871
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Contextual Directed Acyclic Graphs
Ryan Thompson, Edwin V. Bonilla, Robert Kohn; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2872-2880
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Conformalized Semi-supervised Random Forest for Classification and Abnormality Detection
Yujin Han, Mingwenchan Xu, Leying Guan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2881-2889
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Multi-Level Symbolic Regression: Function Structure Learning for Multi-Level Data
Kei Sen Fong, Mehul Motani; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2890-2898
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Non-Convex Joint Community Detection and Group Synchronization via Generalized Power Method
Sijin Chen, Xiwei Cheng, Anthony Man-Cho So; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2899-2907
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Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging
Chung-En Tsai, Hao-Chung Cheng, Yen-Huan Li; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2908-2916
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Discriminant Distance-Aware Representation on Deterministic Uncertainty Quantification Methods
Jiaxin Zhang, Kamalika Das, Sricharan Kumar; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2917-2925
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Estimating treatment effects from single-arm trials via latent-variable modeling
Manuel Haussmann, Tran Minh Son Le, Viivi Halla-aho, Samu Kurki, Jussi Leinonen, Miika Koskinen, Samuel Kaski, Harri Lähdesmäki; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2926-2934
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Unveiling Latent Causal Rules: A Temporal Point Process Approach for Abnormal Event Explanation
Yiling Kuang, Chao Yang, Yang Yang, Shuang Li; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2935-2943
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Online Learning of Decision Trees with Thompson Sampling
Ayman Chaouki, Jesse Read, Albert Bifet; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2944-2952
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Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias
Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2953-2961
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SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits
Subhojyoti Mukherjee, Qiaomin Xie, Josiah P Hanna, Robert Nowak; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2962-2970
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Spectrum Extraction and Clipping for Implicitly Linear Layers
Ali Ebrahimpour Boroojeny, Matus Telgarsky, Hari Sundaram; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2971-2979
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Pessimistic Off-Policy Multi-Objective Optimization
Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy, Lalit Jain, Branislav Kveton, Ge Liu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2980-2988
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Faithful graphical representations of local independence
Søren W. Mogensen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2989-2997
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Density-Regression: Efficient and Distance-aware Deep Regressor for Uncertainty Estimation under Distribution Shifts
Ha Manh Bui, Anqi Liu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2998-3006
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Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures
Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3007-3015
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On the connection between Noise-Contrastive Estimation and Contrastive Divergence
Amanda Olmin, Jakob Lindqvist, Lennart Svensson, Fredrik Lindsten; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3016-3024
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Reward-Relevance-Filtered Linear Offline Reinforcement Learning
Angela Zhou; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3025-3033
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Preventing Arbitrarily High Confidence on Far-Away Data in Point-Estimated Discriminative Neural Networks
Ahmad Rashid, Serena Hacker, Guojun Zhang, Agustinus Kristiadi, Pascal Poupart; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3034-3042
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Stochastic Multi-Armed Bandits with Strongly Reward-Dependent Delays
Yifu Tang, Yingfei Wang, Zeyu Zheng; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3043-3051
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A Greedy Approximation for k-Determinantal Point Processes
Julia Grosse, Rahel Fischer, Roman Garnett, Philipp Hennig; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3052-3060
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Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition
Long-Fei Li, Peng Zhao, Zhi-Hua Zhou; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3061-3069
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Learning the Pareto Set Under Incomplete Preferences: Pure Exploration in Vector Bandits
Efe Mert Karagözlü, Yaşar Cahit Yıldırım, Cağın Ararat, Cem Tekin; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3070-3078
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The Relative Gaussian Mechanism and its Application to Private Gradient Descent
Hadrien Hendrikx, Paul Mangold, Aurélien Bellet; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3079-3087
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Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers
Pim de Haan, Taco Cohen, Johann Brehmer; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3088-3096
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Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes
Washim U. Mondal, Vaneet Aggarwal; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3097-3105
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Learning Fair Division from Bandit Feedback
Hakuei Yamada, Junpei Komiyama, Kenshi Abe, Atsushi Iwasaki; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3106-3114
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Optimal Transport for Measures with Noisy Tree Metric
Tam Le, Truyen Nguyen, Kenji Fukumizu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3115-3123
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Causally Inspired Regularization Enables Domain General Representations
Olawale Salaudeen, Sanmi Koyejo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3124-3132
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Probabilistic Calibration by Design for Neural Network Regression
Victor Dheur, Souhaib Ben Taieb; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3133-3141
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Multi-Agent Learning in Contextual Games under Unknown Constraints
Anna M. Maddux, Maryam Kamgarpour; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3142-3150
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A Scalable Algorithm for Individually Fair k-Means Clustering
MohammadHossein Bateni, Vincent Cohen-Addad, Alessandro Epasto, Silvio Lattanzi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3151-3159
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Approximate Control for Continuous-Time POMDPs
Yannick Eich, Bastian Alt, Heinz Koeppl; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3160-3168
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Offline Primal-Dual Reinforcement Learning for Linear MDPs
Germano Gabbianelli, Gergely Neu, Matteo Papini, Nneka M Okolo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3169-3177
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Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity
Vincent Souveton, Arnaud Guillin, Jens Jasche, Guilhem Lavaux, Manon Michel; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3178-3186
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Learning Unknown Intervention Targets in Structural Causal Models from Heterogeneous Data
Yuqin Yang, Saber Salehkaleybar, Negar Kiyavash; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3187-3195
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XB-MAML: Learning Expandable Basis Parameters for Effective Meta-Learning with Wide Task Coverage
Jae-Jun Lee, Sung Whan Yoon; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3196-3204
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General Tail Bounds for Non-Smooth Stochastic Mirror Descent
Khaled Eldowa, Andrea Paudice; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3205-3213
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Symmetric Equilibrium Learning of VAEs
Boris Flach, Dmitrij Schlesinger, Alexander Shekhovtsov; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3214-3222
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On Feynman-Kac training of partial Bayesian neural networks
Zheng Zhao, Sebastian Mair, Thomas B. Schön, Jens Sjölund; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3223-3231
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No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints
Arpan Losalka, Jonathan Scarlett; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3232-3240
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Learning multivariate temporal point processes via the time-change theorem
Guilherme Augusto Zagatti, See Kiong Ng, Stéphane Bressan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3241-3249
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Model-based Policy Optimization under Approximate Bayesian Inference
Chaoqi Wang, Yuxin Chen, Kevin Murphy; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3250-3258
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SDMTR: A Brain-inspired Transformer for Relation Inference
Xiangyu Zeng, Jie Lin, Piao Hu, Zhihao Li, Tianxi Huang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3259-3267
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Directed Hypergraph Representation Learning for Link Prediction
Zitong Ma, Wenbo Zhao, Zhe Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3268-3276
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Formal Verification of Unknown Stochastic Systems via Non-parametric Estimation
Zhi Zhang, Chenyu Ma, Saleh Soudijani, Sadegh Soudjani; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3277-3285
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Variational Resampling
Oskar Kviman, Nicola Branchini, Víctor Elvira, Jens Lagergren; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3286-3294
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Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training
Tom Sander, Maxime Sylvestre, Alain Durmus; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3295-3303
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Training a Tucker Model With Shared Factors: a Riemannian Optimization Approach
Ivan Peshekhonov, Aleksey Arzhantsev, Maxim Rakhuba; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3304-3312
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Don’t Be Pessimistic Too Early: Look K Steps Ahead!
Chaoqi Wang, Ziyu Ye, Kevin Murphy, Yuxin Chen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3313-3321
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How does GPT-2 Predict Acronyms? Extracting and Understanding a Circuit via Mechanistic Interpretability
Jorge García-Carrasco, Alejandro Maté, Juan Carlos Trujillo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3322-3330
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Identifiable Feature Learning for Spatial Data with Nonlinear ICA
Hermanni Hälvä, Jonathan So, Richard E. Turner, Aapo Hyvärinen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3331-3339
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Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data
Srikar Katta, Harsh Parikh, Cynthia Rudin, Alexander Volfovsky; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3340-3348
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Score Operator Newton transport
Nisha Chandramoorthy, Florian T Schaefer, Youssef M Marzouk; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3349-3357
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ALAS: Active Learning for Autoconversion Rates Prediction from Satellite Data
Maria C. Novitasari, Johannes Quaas, Miguel Rodrigues; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3358-3366
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Optimal Budgeted Rejection Sampling for Generative Models
Alexandre Verine, Muni Sreenivas Pydi, Benjamin Negrevergne, Yann Chevaleyre; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3367-3375
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Posterior Uncertainty Quantification in Neural Networks using Data Augmentation
Luhuan Wu, Sinead A Williamson; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3376-3384
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DHMConv: Directed Hypergraph Momentum Convolution Framework
Wenbo Zhao, Zitong Ma, Zhe Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3385-3393
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From Data Imputation to Data Cleaning — Automated Cleaning of Tabular Data Improves Downstream Predictive Performance
Sebastian Jäger, Felix Biessmann; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3394-3402
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Discriminator Guidance for Autoregressive Diffusion Models
Filip Ekström Kelvinius, Fredrik Lindsten; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3403-3411
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Resilient Constrained Reinforcement Learning
Dongsheng Ding, Zhengyan Huan, Alejandro Ribeiro; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3412-3420
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On-Demand Federated Learning for Arbitrary Target Class Distributions
Isu Jeong, Seulki Lee; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3421-3429
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DiffRed: Dimensionality reduction guided by stable rank
Prarabdh Shukla, Gagan Raj Gupta, Kunal Dutta; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3430-3438
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Data-Driven Confidence Intervals with Optimal Rates for the Mean of Heavy-Tailed Distributions
Ambrus Tamás, Szabolcs Szentpéteri, Balázs Csáji; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3439-3447
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Communication-Efficient Federated Learning With Data and Client Heterogeneity
Hossein Zakerinia, Shayan Talaei, Giorgi Nadiradze, Dan Alistarh; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3448-3456
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SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
Yann Fraboni, Martin Van Waerebeke, Kevin Scaman, Richard Vidal, Laetitia Kameni, Marco Lorenzi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3457-3465
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Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors
Teodora Popordanoska, Sebastian Gregor Gruber, Aleksei Tiulpin, Florian Buettner, Matthew B. Blaschko; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3466-3474
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Learning to Defer to a Population: A Meta-Learning Approach
Dharmesh Tailor, Aditya Patra, Rajeev Verma, Putra Manggala, Eric Nalisnick; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3475-3483
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Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression
Kevin Li, Max Balakirsky, Simon Mak; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3484-3492
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Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence
Ilyas Fatkhullin, Niao He; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3493-3501
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Cylindrical Thompson Sampling for High-Dimensional Bayesian Optimization
Bahador Rashidi, Kerrick Johnstonbaugh, Chao Gao; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3502-3510
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On learning history-based policies for controlling Markov decision processes
Gandharv Patil, Aditya Mahajan, Doina Precup; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3511-3519
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SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification
Patrick Kolpaczki, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3520-3528
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Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation
Vinod Kumar Chauhan, Jiandong Zhou, Ghadeer Ghosheh, Soheila Molaei, David A Clifton; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3529-3537
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Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds
Alexandra Maria Hotti, Lennart Alexander Van der Goten, Jens Lagergren; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3538-3546
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Length independent PAC-Bayes bounds for Simple RNNs
Volodimir Mitarchuk, Clara Lacroce, Rémi Eyraud, Rémi Emonet, Amaury Habrard, Guillaume Rabusseau; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3547-3555
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Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks
Hristo Papazov, Scott Pesme, Nicolas Flammarion; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3556-3564
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Why is parameter averaging beneficial in SGD? An objective smoothing perspective
Atsushi Nitanda, Ryuhei Kikuchi, Shugo Maeda, Denny Wu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3565-3573
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Identification and Estimation of “Causes of Effects” using Covariate-Mediator Information
Ryusei Shingaki, Manabu Kuroki; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3574-3582
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Sequential learning of the Pareto front for multi-objective bandits
élise crepon, Aurélien Garivier, Wouter M Koolen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3583-3591
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Equivalence Testing: The Power of Bounded Adaptivity
Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar, Kuldeep Meel; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3592-3600
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Shape Arithmetic Expressions: Advancing Scientific Discovery Beyond Closed-Form Equations
Krzysztof Kacprzyk, Mihaela van der Schaar; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3601-3609
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On the estimation of persistence intensity functions and linear representations of persistence diagrams
Weichen Wu, Jisu Kim, Alessandro Rinaldo; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3610-3618
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Optimal estimation of Gaussian (poly)trees
Yuhao Wang, Ming Gao, Wai Ming Tai, Bryon Aragam, Arnab Bhattacharyya; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3619-3627
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Approximate Bayesian Class-Conditional Models under Continuous Representation Shift
Thomas L. Lee, Amos Storkey; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3628-3636
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Dissimilarity Bandits
Paolo Battellani, Alberto Maria Metelli, Francesco Trovò; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3637-3645
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Consistent Optimal Transport with Empirical Conditional Measures
Piyushi Manupriya, Rachit K. Das, Sayantan Biswas, SakethaNath N Jagarlapudi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3646-3654
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On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions
Simon Martin, Francis Bach, Giulio Biroli; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3655-3663
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Mixed Models with Multiple Instance Learning
Jan P. Engelmann, Alessandro Palma, Jakub M. Tomczak, Fabian Theis, Francesco Paolo Casale; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3664-3672
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Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation
Jiayi Huang, Han Zhong, Liwei Wang, Lin Yang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3673-3681
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Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalities
Konstantinos Emmanouilidis, Rene Vidal, Nicolas Loizou; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3682-3690
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Inconsistency of Cross-Validation for Structure Learning in Gaussian Graphical Models
Zhao Lyu, Wai Ming Tai, Mladen Kolar, Bryon Aragam; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3691-3699
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Differentially Private Conditional Independence Testing
Iden Kalemaj, Shiva Kasiviswanathan, Aaditya Ramdas; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3700-3708
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Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles
Kevin Scaman, Mathieu Even, Batiste Le Bars, Laurent Massoulie; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3709-3717
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On the Nyström Approximation for Preconditioning in Kernel Machines
Amirhesam Abedsoltan, Parthe Pandit, Luis Rademacher, Mikhail Belkin; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3718-3726
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Learning to Rank for Optimal Treatment Allocation Under Resource Constraints
Fahad Kamran, Maggie Makar, Jenna Wiens; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3727-3735
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Fair Machine Unlearning: Data Removal while Mitigating Disparities
Alex Oesterling, Jiaqi Ma, Flavio Calmon, Himabindu Lakkaraju; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3736-3744
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On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective
Yipei Wang, Xiaoqian Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3745-3753
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Hodge-Compositional Edge Gaussian Processes
Maosheng Yang, Viacheslav Borovitskiy, Elvin Isufi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3754-3762
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Manifold-Aligned Counterfactual Explanations for Neural Networks
Asterios Tsiourvas, Wei Sun, Georgia Perakis; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3763-3771
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Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent
Jialun Zhang, Richard Y Zhang, Hong-Ming Chiu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3772-3780
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LP-based Construction of DC Decompositions for Efficient Inference of Markov Random Fields
Chaitanya Murti, Dhruva Kashyap, Chiranjib Bhattacharyya; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3781-3789
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On the Misspecification of Linear Assumptions in Synthetic Controls
Achille O. R. Nazaret, Claudia Shi, David Blei; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3790-3798
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The sample complexity of ERMs in stochastic convex optimization
Daniel Carmon, Amir Yehudayoff, Roi Livni; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3799-3807
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Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning
Amey P. Pasarkar, Adji Bousso Dieng; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3808-3816
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On cyclical MCMC sampling
Liwei Wang, Xinru Liu, Aaron Smith, Aguemon Y Atchade; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3817-3825
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FairRR: Pre-Processing for Group Fairness through Randomized Response
Joshua John Ward, Xianli Zeng, Guang Cheng; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3826-3834
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Fitting ARMA Time Series Models without Identification: A Proximal Approach
Yin Liu, Sam Davanloo Tajbakhsh; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3835-3843
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Unsupervised Change Point Detection in Multivariate Time Series
Daoping Wu, Suhas Gundimeda, Shaoshuai Mou, Christopher Quinn; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3844-3852
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Proving Linear Mode Connectivity of Neural Networks via Optimal Transport
Damien Ferbach, Baptiste Goujaud, Gauthier Gidel, Aymeric Dieuleveut; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3853-3861
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Multi-objective Optimization via Wasserstein-Fisher-Rao Gradient Flow
Yinuo Ren, Tesi Xiao, Tanmay Gangwani, Anshuka Rangi, Holakou Rahmanian, Lexing Ying, Subhajit Sanyal; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3862-3870
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Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization
Thomas Guilmeau, Nicola Branchini, Emilie Chouzenoux, Victor Elvira; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3871-3879
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A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent
Mehdi Jafarnia Jahromi, Rahul A Jain, Ashutosh Nayyar; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3880-3888
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Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games
Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3889-3897
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Multi-Agent Bandit Learning through Heterogeneous Action Erasure Channels
Osama A Hanna, Merve Karakas, Lin Yang, Christina Fragouli; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3898-3906
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Efficient Variational Sequential Information Control
Jianwei Shen, Jason Pacheco; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3907-3915
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Conditions on Preference Relations that Guarantee the Existence of Optimal Policies
Jonathan Colaço Carr, Prakash Panangaden, Doina Precup; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3916-3924
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Membership Testing in Markov Equivalence Classes via Independence Queries
Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3925-3933
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Functional Flow Matching
Gavin Kerrigan, Giosue Migliorini, Padhraic Smyth; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3934-3942
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Learning Under Random Distributional Shifts
Kirk C. Bansak, Elisabeth Paulson, Dominik Rothenhaeusler; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3943-3951
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Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks
Kaiting Liu, Zahra Atashgahi, Ghada Sokar, Mykola Pechenizkiy, Decebal Constantin Mocanu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3952-3960
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Proxy Methods for Domain Adaptation
Katherine Tsai, Stephen R Pfohl, Olawale Salaudeen, Nicole Chiou, Matt Kusner, Alexander D’Amour, Sanmi Koyejo, Arthur Gretton; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3961-3969
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Contextual Bandits with Budgeted Information Reveal
Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu, Susan Murphy; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3970-3978
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Timing as an Action: Learning When to Observe and Act
Helen Zhou, Audrey Huang, Kamyar Azizzadenesheli, David Childers, Zachary Lipton; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3979-3987
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Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
Wei Shen, Minhui Huang, Jiawei Zhang, Cong Shen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3988-3996
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Online multiple testing with e-values
Ziyu Xu, Aaditya Ramdas; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:3997-4005
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Informative Path Planning with Limited Adaptivity
Rayen Tan, Rohan Ghuge, Viswanath Nagarajan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4006-4014
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How Good is a Single Basin?
Kai Lion, Lorenzo Noci, Thomas Hofmann, Gregor Bachmann; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4015-4023
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Independent Learning in Constrained Markov Potential Games
Philip Jordan, Anas Barakat, Niao He; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4024-4032
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NoisyMix: Boosting Model Robustness to Common Corruptions
Benjamin Erichson, Soon Hoe Lim, Winnie Xu, Francisco Utrera, Ziang Cao, Michael Mahoney; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4033-4041
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Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection
Mohammad Mahmudul Alam, Edward Raff, Stella R Biderman, Tim Oates, James Holt; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4042-4050
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On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem
Georg Pichler, Marco Romanelli, Divya Prakash Manivannan, Prashanth Krishnamurthy, Farshad khorrami, Siddharth Garg; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4051-4059
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Acceleration and Implicit Regularization in Gaussian Phase Retrieval
Tyler Maunu, Martin Molina-Fructuoso; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4060-4068
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Low-rank MDPs with Continuous Action Spaces
Miruna Oprescu, Andrew Bennett, Nathan Kallus; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4069-4077
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Deep Learning-Based Alternative Route Computation
Alex Zhai, Dee Guo, Sreenivas Gollapudi, Kostas Kollias, Daniel Delling; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4078-4086
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An Analytic Solution to Covariance Propagation in Neural Networks
Oren Wright, Yorie Nakahira, José M. F. Moura; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4087-4095
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On the Vulnerability of Fairness Constrained Learning to Malicious Noise
Avrim Blum, Princewill Okoroafor, Aadirupa Saha, Kevin M. Stangl; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4096-4104
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Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting
Siyuan Xu, Yucheng Wang, Mingzhou Fan, Byung-Jun Yoon, Xiaoning Qian; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4105-4113
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Think Global, Adapt Local: Learning Locally Adaptive K-Nearest Neighbor Kernel Density Estimators
Kenny Olsen, Rasmus M. Hoeegh Lindrup, Morten Mørup; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4114-4122
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Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements
Emmanouil Vasileios Vlatakis-Gkaragkounis, Angeliki Giannou, Yudong Chen, Qiaomin Xie; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4123-4131
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Self-Compatibility: Evaluating Causal Discovery without Ground Truth
Philipp M. Faller, Leena C. Vankadara, Atalanti A. Mastakouri, Francesco Locatello, Dominik Janzing; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4132-4140
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Equivariant bootstrapping for uncertainty quantification in imaging inverse problems
Marcelo Pereyra, Julián Tachella; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4141-4149
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Private Learning with Public Features
Walid Krichene, Nicolas E Mayoraz, Steffen Rendle, Shuang Song, Abhradeep Thakurta, Li Zhang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4150-4158
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An Improved Algorithm for Learning Drifting Discrete Distributions
Alessio Mazzetto; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4159-4167
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Towards a Complete Benchmark on Video Moment Localization
Jinyeong Chae, Donghwa Kim, Kwanseok Kim, Doyeon Lee, Sangho Lee, Seongsu Ha, Jonghwan Mun, Wooyoung Kang, Byungseok Roh, Joonseok Lee; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4168-4176
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Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems
Neharika Jali, Guannan Qu, Weina Wang, Gauri Joshi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4177-4185
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Sinkhorn Flow as Mirror Flow: A Continuous-Time Framework for Generalizing the Sinkhorn Algorithm
Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4186-4194
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SADI: Similarity-Aware Diffusion Model-Based Imputation for Incomplete Temporal EHR Data
Zongyu Dai, Emily Getzen, Qi Long; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4195-4203
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Weight-Sharing Regularization
Mehran Shakerinava, Motahareh MS Sohrabi, Siamak Ravanbakhsh, Simon Lacoste-Julien; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4204-4212
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Generative Flow Networks as Entropy-Regularized RL
Daniil Tiapkin, Nikita Morozov, Alexey Naumov, Dmitry P Vetrov; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4213-4221
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Multi-resolution Time-Series Transformer for Long-term Forecasting
Yitian Zhang, Liheng Ma, Soumyasundar Pal, Yingxue Zhang, Mark Coates; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4222-4230
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First Passage Percolation with Queried Hints
Kritkorn Karntikoon, Yiheng Shen, Sreenivas Gollapudi, Kostas Kollias, Aaron Schild, Ali K Sinop; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4231-4239
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User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates
Daogao Liu, Hilal Asi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4240-4248
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The Effective Number of Shared Dimensions Between Paired Datasets
Hamza Giaffar, Camille Rullán Buxó, Mikio Aoi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4249-4257
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DE-HNN: An effective neural model for Circuit Netlist representation
Zhishang Luo, Truong Son Hy, Puoya Tabaghi, Michaël Defferrard, Elahe Rezaei, Ryan M. Carey, Rhett Davis, Rajeev Jain, Yusu Wang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4258-4266
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Simulation-Based Stacking
Yuling Yao, Bruno Régaldo-Saint Blancard, Justin Domke; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4267-4275
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Towards Practical Non-Adversarial Distribution Matching
Ziyu Gong, Ben Usman, Han Zhao, David I Inouye; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4276-4284
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Benchmarking Observational Studies with Experimental Data under Right-Censoring
Ilker Demirel, Edward De Brouwer, Zeshan M Hussain, Michael Oberst, Anthony A Philippakis, David Sontag; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4285-4293
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Asynchronous Randomized Trace Estimation
Vasileios Kalantzis, Shashanka Ubaru, Chai Wah Wu, Georgios Kollias, Lior Horesh; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4294-4302
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Computing epidemic metrics with edge differential privacy
George Z. Li, Dung Nguyen, Anil Vullikanti; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4303-4311
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Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference
Declan McNamara, Jackson Loper, Jeffrey Regier; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4312-4320
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Anytime-Constrained Reinforcement Learning
Jeremy McMahan, Xiaojin Zhu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4321-4329
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Tensor-view Topological Graph Neural Network
Tao Wen, Elynn Chen, Yuzhou Chen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4330-4338
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Auditing Fairness under Unobserved Confounding
Yewon Byun, Dylan Sam, Michael Oberst, Zachary Lipton, Bryan Wilder; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4339-4347
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Consistency of Dictionary-Based Manifold Learning
Samson J. Koelle, Hanyu Zhang, Octavian-Vlad Murad, Marina Meila; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4348-4356
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Probabilistic Modeling for Sequences of Sets in Continuous-Time
Yuxin Chang, Alex J Boyd, Padhraic Smyth; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4357-4365
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Causal Q-Aggregation for CATE Model Selection
Hui Lan, Vasilis Syrgkanis; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4366-4374
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Self-Supervised Quantization-Aware Knowledge Distillation
Kaiqi Zhao, Ming Zhao; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4375-4383
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FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning
Xiang Meng, Wenyu Chen, Riade Benbaki, Rahul Mazumder; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4384-4392
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The effect of Leaky ReLUs on the training and generalization of overparameterized networks
Yinglong Guo, Shaohan Li, Gilad Lerman; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4393-4401
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Decentralized Multi-Level Compositional Optimization Algorithms with Level-Independent Convergence Rate
Hongchang Gao; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4402-4410
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Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate
Ruichen Jiang, Parameswaran Raman, Shoham Sabach, Aryan Mokhtari, Mingyi Hong, Volkan Cevher; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4411-4419
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Sampling-based Safe Reinforcement Learning for Nonlinear Dynamical Systems
Wesley Suttle, Vipul Kumar Sharma, Krishna Chaitanya Kosaraju, Sivaranjani Seetharaman, Ji Liu, Vijay Gupta, Brian M Sadler; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4420-4428
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Soft-constrained Schrödinger Bridge: a Stochastic Control Approach
Jhanvi Garg, Xianyang Zhang, Quan Zhou; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4429-4437
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Coreset Markov chain Monte Carlo
Naitong Chen, Trevor Campbell; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4438-4446
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A General Theoretical Paradigm to Understand Learning from Human Preferences
Mohammad Gheshlaghi Azar, Zhaohan Daniel Guo, Bilal Piot, Remi Munos, Mark Rowland, Michal Valko, Daniele Calandriello; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4447-4455
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Policy Learning for Localized Interventions from Observational Data
Myrl G. Marmarelis, Fred Morstatter, Aram Galstyan, Greg Ver Steeg; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4456-4464
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Understanding the Generalization Benefits of Late Learning Rate Decay
Yinuo Ren, Chao Ma, Lexing Ying; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4465-4473
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Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
Junghyun Lee, Se-Young Yun, Kwang-Sung Jun; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4474-4482
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Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization
Yutong Wang, Rishi Sonthalia, Wei Hu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4483-4491
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Identifiability of Product of Experts Models
Manav Kant, Eric Y Ma, Andrei Staicu, Leonard J Schulman, Spencer Gordon; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4492-4500
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Gibbs-Based Information Criteria and the Over-Parameterized Regime
Haobo Chen, Gregory W Wornell, Yuheng Bu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4501-4509
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Improving Robustness via Tilted Exponential Layer: A Communication-Theoretic Perspective
Bhagyashree Puranik, Ahmad Beirami, Yao Qin, Upamanyu Madhow; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4510-4518
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On the Generalization Ability of Unsupervised Pretraining
Yuyang Deng, Junyuan Hong, Jiayu Zhou, Mehrdad Mahdavi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4519-4527
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Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks
Waleed Mustafa, Philipp Liznerski, Antoine Ledent, Dennis Wagner, Puyu Wang, Marius Kloft; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4528-4536
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BLIS-Net: Classifying and Analyzing Signals on Graphs
Charles Xu, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4537-4545
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Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources
Rohan Deb, Aadirupa Saha, Arindam Banerjee; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4546-4554
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Fast Fourier Bayesian Quadrature
Houston Warren, Fabio Ramos; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4555-4563
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Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty
Yu Inatsu, Shion Takeno, Hiroyuki Hanada, Kazuki Iwata, Ichiro Takeuchi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4564-4572
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To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models
Cyrus Cousins, I. Elizabeth Kumar, Suresh Venkatasubramanian; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4573-4581
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Two Birds with One Stone: Enhancing Uncertainty Quantification and Interpretability with Graph Functional Neural Process
Lingkai Kong, Haotian Sun, Yuchen Zhuang, Haorui Wang, Wenhao Mu, Chao Zhang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4582-4590
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Sample Efficient Learning of Factored Embeddings of Tensor Fields
Taemin Heo, Chandrajit Bajaj; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4591-4599
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autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm
Miguel Biron-Lattes, Nikola Surjanovic, Saifuddin Syed, Trevor Campbell, Alexandre Bouchard-Cote; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4600-4608
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Causal Bandits with General Causal Models and Interventions
Zirui Yan, Dennis Wei, Dmitriy A Katz, Prasanna Sattigeri, Ali Tajer; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4609-4617
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Surrogate Active Subspaces for Jump-Discontinuous Functions
Nathan Wycoff; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4618-4626
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Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints
Ahmet Alacaoglu, Stephen J Wright; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4627-4635
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Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs
Mishfad Shaikh Veedu, Deepjyoti Deka, Murti Salapaka; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4636-4644
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Pathwise Explanation of ReLU Neural Networks
Seongwoo Lim, Won Jo, Joohyung Lee, Jaesik Choi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4645-4653
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The AL$\ell_0$CORE Tensor Decomposition for Sparse Count Data
John Hood, Aaron J. Schein; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4654-4662
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Adaptive Federated Minimax Optimization with Lower Complexities
Feihu Huang, Xinrui Wang, Junyi Li, Songcan Chen; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4663-4671
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Mixture-of-Linear-Experts for Long-term Time Series Forecasting
Ronghao Ni, Zinan Lin, Shuaiqi Wang, Giulia Fanti; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4672-4680
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On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: a regret lower bound for WSU-UX
Ali Mortazavi, Junhao Lin, Nishant Mehta; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4681-4689
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Faster Recalibration of an Online Predictor via Approachability
Princewill Okoroafor, Bobby Kleinberg, Wen Sun; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4690-4698
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Provable Policy Gradient Methods for Average-Reward Markov Potential Games
Min Cheng, Ruida Zhou, P. R. Kumar, Chao Tian; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4699-4707
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A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning
Mizhaan P. Maniyar, Prashanth L.A., Akash Mondal, Shalabh Bhatnagar; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4708-4716
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Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach
Juanwu Lu, Wei Zhan, Masayoshi Tomizuka, Yeping Hu; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4717-4725
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Understanding Inverse Scaling and Emergence in Multitask Representation Learning
Muhammed E. Ildiz, Zhe Zhao, Samet Oymak; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4726-4734
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Sharpened Lazy Incremental Quasi-Newton Method
Aakash Sunil Lahoti, Spandan Senapati, Ketan Rajawat, Alec Koppel; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4735-4743
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Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach
Yinan Li, Chicheng Zhang; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4744-4752
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Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention
Anqi Mao, Mehryar Mohri, Yutao Zhong; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4753-4761
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Deep Classifier Mimicry without Data Access
Steven Braun, Martin Mundt, Kristian Kersting; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4762-4770
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Data Driven Threshold and Potential Initialization for Spiking Neural Networks
Velibor Bojkovic, Srinivas Anumasa, Giulia De Masi, Bin Gu, Huan Xiong; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4771-4779
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Revisiting the Noise Model of Stochastic Gradient Descent
Barak Battash, Lior Wolf, Ofir Lindenbaum; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4780-4788
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Warped Diffusion for Latent Differentiation Inference
Masahiro Nakano, Hiroki Sakuma, Ryo Nishikimi, Ryohei Shibue, Takashi Sato, Tomoharu Iwata, Kunio Kashino; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4789-4797
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Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains
Nikita Tsoy, Anna Mihalkova, Teodora N Todorova, Nikola Konstantinov; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4798-4806
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Random Oscillators Network for Time Series Processing
Andrea Ceni, Andrea Cossu, Maximilian W Stölzle, Jingyue Liu, Cosimo Della Santina, Davide Bacciu, Claudio Gallicchio; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4807-4815
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Mitigating Underfitting in Learning to Defer with Consistent Losses
Shuqi Liu, Yuzhou Cao, Qiaozhen Zhang, Lei Feng, Bo An; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4816-4824
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Consistent Hierarchical Classification with A Generalized Metric
Yuzhou Cao, Lei Feng, Bo An; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4825-4833
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SDEs for Minimax Optimization
Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Proske, Aurelien Lucchi; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4834-4842
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Differentially Private Reward Estimation with Preference Feedback
Sayak Ray Chowdhury, Xingyu Zhou, Nagarajan Natarajan; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4843-4851
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Differentiable Rendering with Reparameterized Volume Sampling
Nikita Morozov, Denis Rakitin, Oleg Desheulin, Dmitry P Vetrov, Kirill Struminsky; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4852-4860
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Parameter-Agnostic Optimization under Relaxed Smoothness
Florian Hübler, Junchi Yang, Xiang Li, Niao He; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4861-4869
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Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases
Ruslan Nazykov, Aleksandr Shestakov, Vladimir Solodkin, Aleksandr Beznosikov, Gauthier Gidel, Alexander Gasnikov; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4870-4878
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Efficient Conformal Prediction under Data Heterogeneity
Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horvath, Martin Takac, Eric Moulines, Maxim Panov; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4879-4887
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Sample-efficient neural likelihood-free Bayesian inference of implicit HMMs
Sanmitra Ghosh, Paul Birrell, Daniela De Angelis; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4888-4896
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Identifying Confounding from Causal Mechanism Shifts
Sarah Mameche, Jilles Vreeken, David Kaltenpoth; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4897-4905
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Tight Verification of Probabilistic Robustness in Bayesian Neural Networks
Ben Batten, Mehran Hosseini, Alessio Lomuscio; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4906-4914
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Testing exchangeability by pairwise betting
Aytijhya Saha, Aaditya Ramdas; Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4915-4923
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