JMLR Volume 26
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Efficiently Escaping Saddle Points in Bilevel Optimization
Minhui Huang, Xuxing Chen, Kaiyi Ji, Shiqian Ma, Lifeng Lai (1):1−61, 2025 PDF BibTeX
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Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes
Charles Riou, Pierre Alquier, Badr-Eddine Chérief-Abdellatif (2):1−60, 2025 PDF BibTeX
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DisC2o-HD: Distributed causal inference with covariates shift for analyzing real-world high-dimensional data
Jiayi Tong, Jie Hu, George Hripcsak, Yang Ning, Yong Chen (3):1−50, 2025 PDF BibTeX
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Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization
Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis (4):1−68, 2025 PDF BibTeX
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Enhancing Graph Representation Learning with Localized Topological Features
Zuoyu Yan, Qi Zhao, Ze Ye, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen (5):1−36, 2025 PDF BibTeX
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Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents
Marco Pleines, Matthias Pallasch, Frank Zimmer, Mike Preuss (6):1−40, 2025 codePDF BibTeX
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A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
Hugo Lebeau, Florent Chatelain, Romain Couillet (7):1−64, 2025 PDF BibTeX
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Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
Boxin Zhao, Lingxiao Wang, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Chaochao Chen, Mladen Kolar (8):1−67, 2025 codePDF BibTeX
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Test-Time Training on Video Streams
Renhao Wang, Yu Sun, Arnuv Tandon, Yossi Gandelsman, Xinlei Chen, Alexei A. Efros, Xiaolong Wang (9):1−29, 2025 codePDF BibTeX
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An Axiomatic Definition of Hierarchical Clustering
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Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
Tianyi Lin, Chi Jin, Michael I. Jordan (11):1−45, 2025 PDF BibTeX
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Selective Inference with Distributed Data
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Estimating Network-Mediated Causal Effects via Principal Components Network Regression
Alex Hayes, Mark M. Fredrickson, Keith Levin (13):1−99, 2025 codePDF BibTeX
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Locally Private Causal Inference for Randomized Experiments
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From Sparse to Dense Functional Data in High Dimensions: Revisiting Phase Transitions from a Non-Asymptotic Perspective
Shaojun Guo, Dong Li, Xinghao Qiao, Yizhu Wang (15):1−40, 2025 PDF BibTeX
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Error estimation and adaptive tuning for unregularized robust M-estimator
Pierre C. Bellec, Takuya Koriyama (16):1−40, 2025 PDF BibTeX
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Supervised Learning with Evolving Tasks and Performance Guarantees
Verónica Álvarez, Santiago Mazuelas, Jose A. Lozano (17):1−59, 2025 codePDF BibTeX
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Riemannian Bilevel Optimization
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Random ReLU Neural Networks as Non-Gaussian Processes
Rahul Parhi, Pakshal Bohra, Ayoub El Biari, Mehrsa Pourya, Michael Unser (19):1−31, 2025 PDF BibTeX
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Regularizing Hard Examples Improves Adversarial Robustness
Hyungyu Lee, Saehyung Lee, Ho Bae, Sungroh Yoon (20):1−48, 2025 PDF BibTeX
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Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions
Dapeng Yao, Fangzheng Xie, Yanxun Xu (21):1−50, 2025 PDF BibTeX
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Directed Cyclic Graphs for Simultaneous Discovery of Time-Lagged and Instantaneous Causality from Longitudinal Data Using Instrumental Variables
Wei Jin, Yang Ni, Amanda B. Spence, Leah H. Rubin, Yanxun Xu (22):1−62, 2025 codePDF BibTeX
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Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick
Xiyuan Wang, Pan Li, Muhan Zhang (23):1−44, 2025 codePDF BibTeX
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The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
Shuze Daniel Liu, Shuhang Chen, Shangtong Zhang (24):1−76, 2025 PDF BibTeX
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depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers
Kaichao You, Runsheng Bai, Meng Cao, Jianmin Wang, Ion Stoica, Mingsheng Long (25):1−18, 2025 codePDF BibTeX
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The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
Jiin Woo, Gauri Joshi, Yuejie Chi (26):1−85, 2025 PDF BibTeX
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Mean Aggregator is More Robust than Robust Aggregators under Label Poisoning Attacks on Distributed Heterogeneous Data
Jie Peng, Weiyu Li, Stefan Vlaski, Qing Ling (27):1−51, 2025 codePDF BibTeX
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Optimal Experiment Design for Causal Effect Identification
Sina Akbari, Jalal Etesami, Negar Kiyavash (28):1−56, 2025 codePDF BibTeX
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Orthogonal Bases for Equivariant Graph Learning with Provable k-WL Expressive Power
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Bayesian Multi-Group Gaussian Process Models for Heterogeneous Group-Structured Data
Didong Li, Andrew Jones, Sudipto Banerjee, Barbara E. Engelhardt (30):1−34, 2025 codePDF BibTeX
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Accelerating optimization over the space of probability measures
Shi Chen, Qin Li, Oliver Tse, Stephen J. Wright (31):1−40, 2025 PDF BibTeX
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Sliced-Wasserstein Distances and Flows on Cartan-Hadamard Manifolds
Clément Bonet, Lucas Drumetz, Nicolas Courty (32):1−76, 2025 codePDF BibTeX
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Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
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gsplat: An Open-Source Library for Gaussian Splatting
Vickie Ye, Ruilong Li, Justin Kerr, Matias Turkulainen, Brent Yi, Zhuoyang Pan, Otto Seiskari, Jianbo Ye, Jeffrey Hu, Matthew Tancik, Angjoo Kanazawa (34):1−17, 2025 codePDF BibTeX