[](/)
[Home Page](/)
[Papers](/papers)
[Submissions](/author-info.html)
[News](/news.html)
[Editorial Board](/editorial-board.html)
[Special Issues](/special_issues/)
[Open Source Software](/mloss)
[Proceedings (PMLR)](https://proceedings.mlr.press/)
[Data (DMLR)](https://data.mlr.press/)
[Transactions (TMLR)](/tmlr)
[Search](/search-jmlr.html)
[Statistics](/stats.html)
[Login](/manudb)
[Frequently Asked Questions](/faq.html)
[Contact Us](/contact.html)
[](/jmlr.xml)
Journal of Machine Learning Research
====================================
The Journal of Machine Learning Research (JMLR), [established in 2000](/history.html), provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online.
JMLR has a commitment to rigorous yet rapid reviewing. Final versions are [published electronically](papers) (ISSN 1533-7928) immediately upon receipt. Until the end of 2004, paper volumes (ISSN 1532-4435) were published 8 times annually and sold to libraries and individuals by the MIT Press. Paper volumes (ISSN 1532-4435) are now published and sold by [Microtome Publishing](http://www.mtome.com/).
News
----
* _2025.02.10_: [Volume 25](/papers/v25) completed; [Volume 26](/papers/v26) began.
* _2024.02.18_: [Volume 24](/papers/v24) completed; [Volume 25](/papers/v25) began.
* _2023.01.20_: [Volume 23](/papers/v23) completed; [Volume 24](/papers/v24) began.
* _2022.07.20_: New [special issue on climate change](/special_issues/climate_change.html).
* _2022.02.18_: New blog post: [Retrospectives from 20 Years of JMLR](/news/2022/retrospectives.html) .
* _2022.01.25_: [Volume 22](/papers/v22) completed; [Volume 23](/papers/v23) began.
* _2021.12.02_: [Message from outgoing co-EiC Bernhard Schölkopf](news/2021/schoelkopf-retirement.html).
* _2021.02.10_: [Volume 21](/papers/v21) completed; [Volume 22](/papers/v22) began.
* [More news ...](/news.html)
Latest papers
-------------
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_**, 2025. [_(Machine Learning Open Source Software Paper)_](http://www.jmlr.org/mloss/)
\[[abs](/papers/v26/24-1476.html)\]\[[pdf](/papers/volume26/24-1476/24-1476.pdf)\]\[[bib](/papers/v26/24-1476.bib)\] \[[code](https://github.com/nerfstudio-project/gsplat/)\]
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
**_Sen Na, Michael Mahoney_**, 2025.
\[[abs](/papers/v26/24-0530.html)\]\[[pdf](/papers/volume26/24-0530/24-0530.pdf)\]\[[bib](/papers/v26/24-0530.bib)\]
Sliced-Wasserstein Distances and Flows on Cartan-Hadamard Manifolds
**_Clément Bonet, Lucas Drumetz, Nicolas Courty_**, 2025.
\[[abs](/papers/v26/24-0359.html)\]\[[pdf](/papers/volume26/24-0359/24-0359.pdf)\]\[[bib](/papers/v26/24-0359.bib)\] \[[code](https://github.com/clbonet/sliced-wasserstein_distances_and_flows_on_cartan-hadamard_manifolds)\]
Accelerating optimization over the space of probability measures
**_Shi Chen, Qin Li, Oliver Tse, Stephen J. Wright_**, 2025.
\[[abs](/papers/v26/23-1288.html)\]\[[pdf](/papers/volume26/23-1288/23-1288.pdf)\]\[[bib](/papers/v26/23-1288.bib)\]
Bayesian Multi-Group Gaussian Process Models for Heterogeneous Group-Structured Data
**_Didong Li, Andrew Jones, Sudipto Banerjee, Barbara E. Engelhardt_**, 2025.
\[[abs](/papers/v26/23-0291.html)\]\[[pdf](/papers/volume26/23-0291/23-0291.pdf)\]\[[bib](/papers/v26/23-0291.bib)\] \[[code](https://github.com/andrewcharlesjones/multi-group-GP)\]
Orthogonal Bases for Equivariant Graph Learning with Provable k-WL Expressive Power
**_Jia He, Maggie Cheng_**, 2025.
\[[abs](/papers/v26/23-0178.html)\]\[[pdf](/papers/volume26/23-0178/23-0178.pdf)\]\[[bib](/papers/v26/23-0178.bib)\]
Optimal Experiment Design for Causal Effect Identification
**_Sina Akbari, Jalal Etesami, Negar Kiyavash_**, 2025.
\[[abs](/papers/v26/22-1516.html)\]\[[pdf](/papers/volume26/22-1516/22-1516.pdf)\]\[[bib](/papers/v26/22-1516.bib)\] \[[code](https://github.com/SinaAkbarii/min_cost_intervention)\]
Mean Aggregator is More Robust than Robust Aggregators under Label Poisoning Attacks on Distributed Heterogeneous Data
**_Jie Peng, Weiyu Li, Stefan Vlaski, Qing Ling_**, 2025.
\[[abs](/papers/v26/24-1307.html)\]\[[pdf](/papers/volume26/24-1307/24-1307.pdf)\]\[[bib](/papers/v26/24-1307.bib)\] \[[code](https://github.com/pengj97/LPA)\]
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond
**_Jiin Woo, Gauri Joshi, Yuejie Chi_**, 2025.
\[[abs](/papers/v26/24-0579.html)\]\[[pdf](/papers/volume26/24-0579/24-0579.pdf)\]\[[bib](/papers/v26/24-0579.bib)\]
depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers
**_Kaichao You, Runsheng Bai, Meng Cao, Jianmin Wang, Ion Stoica, Mingsheng Long_**, 2025. [_(Machine Learning Open Source Software Paper)_](http://www.jmlr.org/mloss/)
\[[abs](/papers/v26/24-0383.html)\]\[[pdf](/papers/volume26/24-0383/24-0383.pdf)\]\[[bib](/papers/v26/24-0383.bib)\] \[[code](https://github.com/thuml/depyf)\]
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise
**_Shuze Daniel Liu, Shuhang Chen, Shangtong Zhang_**, 2025.
\[[abs](/papers/v26/24-0100.html)\]\[[pdf](/papers/volume26/24-0100/24-0100.pdf)\]\[[bib](/papers/v26/24-0100.bib)\]
Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick
**_Xiyuan Wang, Pan Li, Muhan Zhang_**, 2025.
\[[abs](/papers/v26/23-0560.html)\]\[[pdf](/papers/volume26/23-0560/23-0560.pdf)\]\[[bib](/papers/v26/23-0560.bib)\] \[[code](https://github.com/GraphPKU/LabelingTrick)\]
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_**, 2025.
\[[abs](/papers/v26/23-0272.html)\]\[[pdf](/papers/volume26/23-0272/23-0272.pdf)\]\[[bib](/papers/v26/23-0272.bib)\] \[[code](https://github.com/bluejw/BayesDCG)\]
Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions
**_Dapeng Yao, Fangzheng Xie, Yanxun Xu_**, 2025.
\[[abs](/papers/v26/23-0142.html)\]\[[pdf](/papers/volume26/23-0142/23-0142.pdf)\]\[[bib](/papers/v26/23-0142.bib)\]
Regularizing Hard Examples Improves Adversarial Robustness
**_Hyungyu Lee, Saehyung Lee, Ho Bae, Sungroh Yoon_**, 2025.
\[[abs](/papers/v26/22-1428.html)\]\[[pdf](/papers/volume26/22-1428/22-1428.pdf)\]\[[bib](/papers/v26/22-1428.bib)\]
Random ReLU Neural Networks as Non-Gaussian Processes
**_Rahul Parhi, Pakshal Bohra, Ayoub El Biari, Mehrsa Pourya, Michael Unser_**, 2025.
\[[abs](/papers/v26/24-0737.html)\]\[[pdf](/papers/volume26/24-0737/24-0737.pdf)\]\[[bib](/papers/v26/24-0737.bib)\]
Riemannian Bilevel Optimization
**_Jiaxiang Li, Shiqian Ma_**, 2025.
\[[abs](/papers/v26/24-0397.html)\]\[[pdf](/papers/volume26/24-0397/24-0397.pdf)\]\[[bib](/papers/v26/24-0397.bib)\] \[[code](https://github.com/JasonJiaxiangLi/Manifold_bilevel)\]
Supervised Learning with Evolving Tasks and Performance Guarantees
**_Verónica Álvarez, Santiago Mazuelas, Jose A. Lozano_**, 2025.
\[[abs](/papers/v26/24-0343.html)\]\[[pdf](/papers/volume26/24-0343/24-0343.pdf)\]\[[bib](/papers/v26/24-0343.bib)\] \[[code](https://github.com/MachineLearningBCAM/Supervised-learning-evolving-task-JMLR-2025)\]
Error estimation and adaptive tuning for unregularized robust M-estimator
**_Pierre C. Bellec, Takuya Koriyama_**, 2025.
\[[abs](/papers/v26/24-0060.html)\]\[[pdf](/papers/volume26/24-0060/24-0060.pdf)\]\[[bib](/papers/v26/24-0060.bib)\]
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_**, 2025.
\[[abs](/papers/v26/23-1578.html)\]\[[pdf](/papers/volume26/23-1578/23-1578.pdf)\]\[[bib](/papers/v26/23-1578.bib)\]
Locally Private Causal Inference for Randomized Experiments
**_Yuki Ohnishi, Jordan Awan_**, 2025.
\[[abs](/papers/v26/23-1401.html)\]\[[pdf](/papers/volume26/23-1401/23-1401.pdf)\]\[[bib](/papers/v26/23-1401.bib)\]
Estimating Network-Mediated Causal Effects via Principal Components Network Regression
**_Alex Hayes, Mark M. Fredrickson, Keith Levin_**, 2025.
\[[abs](/papers/v26/23-1317.html)\]\[[pdf](/papers/volume26/23-1317/23-1317.pdf)\]\[[bib](/papers/v26/23-1317.bib)\] \[[code](https://github.com/alexpghayes/network-mediation-replication)\]
Selective Inference with Distributed Data
**_Sifan Liu, Snigdha Panigrahi_**, 2025.
\[[abs](/papers/v26/23-0309.html)\]\[[pdf](/papers/volume26/23-0309/23-0309.pdf)\]\[[bib](/papers/v26/23-0309.bib)\] \[[code](https://github.com/snigdhagit/Distributed-Selectinf)\]
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
**_Tianyi Lin, Chi Jin, Michael I. Jordan_**, 2025.
\[[abs](/papers/v26/22-0863.html)\]\[[pdf](/papers/volume26/22-0863/22-0863.pdf)\]\[[bib](/papers/v26/22-0863.bib)\]
An Axiomatic Definition of Hierarchical Clustering
**_Ery Arias-Castro, Elizabeth Coda_**, 2025.
\[[abs](/papers/v26/24-1052.html)\]\[[pdf](/papers/volume26/24-1052/24-1052.pdf)\]\[[bib](/papers/v26/24-1052.bib)\]
Test-Time Training on Video Streams
**_Renhao Wang, Yu Sun, Arnuv Tandon, Yossi Gandelsman, Xinlei Chen, Alexei A. Efros, Xiaolong Wang_**, 2025.
\[[abs](/papers/v26/24-0439.html)\]\[[pdf](/papers/volume26/24-0439/24-0439.pdf)\]\[[bib](/papers/v26/24-0439.bib)\] \[[code](https://test-time-training.github.io/video)\]
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_**, 2025.
\[[abs](/papers/v26/24-0385.html)\]\[[pdf](/papers/volume26/24-0385/24-0385.pdf)\]\[[bib](/papers/v26/24-0385.bib)\] \[[code](https://github.com/boxinz17/FL-Client-Sampling)\]
A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation
**_Hugo Lebeau, Florent Chatelain, Romain Couillet_**, 2025.
\[[abs](/papers/v26/24-0193.html)\]\[[pdf](/papers/volume26/24-0193/24-0193.pdf)\]\[[bib](/papers/v26/24-0193.bib)\]
Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents
**_Marco Pleines, Matthias Pallasch, Frank Zimmer, Mike Preuss_**, 2025.
\[[abs](/papers/v26/24-0043.html)\]\[[pdf](/papers/volume26/24-0043/24-0043.pdf)\]\[[bib](/papers/v26/24-0043.bib)\] \[[code](https://marcometer.github.io/jmlr_2024.github.io/)\]
Enhancing Graph Representation Learning with Localized Topological Features
**_Zuoyu Yan, Qi Zhao, Ze Ye, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen_**, 2025.
\[[abs](/papers/v26/23-1424.html)\]\[[pdf](/papers/volume26/23-1424/23-1424.pdf)\]\[[bib](/papers/v26/23-1424.bib)\]
Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization
**_Antoine de Mathelin, François Deheeger, Mathilde Mougeot, Nicolas Vayatis_**, 2025.
\[[abs](/papers/v26/23-1359.html)\]\[[pdf](/papers/volume26/23-1359/23-1359.pdf)\]\[[bib](/papers/v26/23-1359.bib)\]
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_**, 2025.
\[[abs](/papers/v26/23-1254.html)\]\[[pdf](/papers/volume26/23-1254/23-1254.pdf)\]\[[bib](/papers/v26/23-1254.bib)\]
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_**, 2025.
\[[abs](/papers/v26/23-025.html)\]\[[pdf](/papers/volume26/23-025/23-025.pdf)\]\[[bib](/papers/v26/23-025.bib)\]
Efficiently Escaping Saddle Points in Bilevel Optimization
**_Minhui Huang, Xuxing Chen, Kaiyi Ji, Shiqian Ma, Lifeng Lai_**, 2025.
\[[abs](/papers/v26/22-0136.html)\]\[[pdf](/papers/volume26/22-0136/22-0136.pdf)\]\[[bib](/papers/v26/22-0136.bib)\]
[Full list](/papers/)
© [JMLR](https://www.jmlr.org) 2025.
[Mastodon](https://sigmoid.social/@jmlr)