JMLR Volume 26
- Efficiently Escaping Saddle Points in Bilevel Optimization
- Minhui Huang, Xuxing Chen, Kaiyi Ji, Shiqian Ma, Lifeng Lai; (1):1−61, 2025.
[abs][pdf][bib]
- 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.
[abs][pdf][bib]
- 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.
[abs][pdf][bib]
- Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization
- Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis; (4):1−68, 2025.
[abs][pdf][bib]
- 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.
[abs][pdf][bib]
- Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents
- Marco Pleines, Matthias Pallasch, Frank Zimmer, Mike Preuss; (6):1−40, 2025.
[abs][pdf][bib]
[code]
- A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
- Hugo Lebeau, Florent Chatelain, Romain Couillet; (7):1−64, 2025.
[abs][pdf][bib]
- 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.
[abs][pdf][bib]
[code]
- 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.
[abs][pdf][bib]
[code]
- An Axiomatic Definition of Hierarchical Clustering
- Ery Arias-Castro, Elizabeth Coda; (10):1−26, 2025.
[abs][pdf][bib]
- Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
- Tianyi Lin, Chi Jin, Michael I. Jordan; (11):1−45, 2025.
[abs][pdf][bib]
- Selective Inference with Distributed Data
- Sifan Liu, Snigdha Panigrahi; (12):1−44, 2025.
[abs][pdf][bib]
[code]
- Estimating Network-Mediated Causal Effects via Principal Components Network Regression
- Alex Hayes, Mark M. Fredrickson, Keith Levin; (13):1−99, 2025.
[abs][pdf][bib]
[code]
- Locally Private Causal Inference for Randomized Experiments
- Yuki Ohnishi, Jordan Awan; (14):1−40, 2025.
[abs][pdf][bib]
- 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.
[abs][pdf][bib]
- Error estimation and adaptive tuning for unregularized robust M-estimator
- Pierre C. Bellec, Takuya Koriyama; (16):1−40, 2025.
[abs][pdf][bib]
- Supervised Learning with Evolving Tasks and Performance Guarantees
- Verónica Álvarez, Santiago Mazuelas, Jose A. Lozano; (17):1−59, 2025.
[abs][pdf][bib]
[code]
- Riemannian Bilevel Optimization
- Jiaxiang Li, Shiqian Ma; (18):1−44, 2025.
[abs][pdf][bib]
[code]
- Random ReLU Neural Networks as Non-Gaussian Processes
- Rahul Parhi, Pakshal Bohra, Ayoub El Biari, Mehrsa Pourya, Michael Unser; (19):1−31, 2025.
[abs][pdf][bib]
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