JMLR

Invariant kernels on the space of complex covariance matrices

Salem Said, Franziskus Steinert, Cyrus Mostajeran

Comments under review Journal of Machine Learning Research

A Comparative Evaluation of Quantification Methods

Tobias Schumacher, Markus Strohmaier, Florian Lemmerich

Comments 41 pages, 18 figures, 9 tables

Journal ref Journal of Machine Learning Research, Volume 26, Article 55 (2025), 54 pages

On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems

Michael Muehlebach, Michael I. Jordan

Comments 47 pages, 11 figures

Journal ref Journal of Machine Learning Research, 23(256):1-47, 2022

Extremal graphical modeling with latent variables via convex optimization

Sebastian Engelke, Armeen Taeb

Comments Journal of Machine Learning Research, 2025

Distributed Stochastic Bilevel Optimization: Improved Complexity and Heterogeneity Analysis

Youcheng Niu, Jinming Xu, Ying Sun, Yan Huang, Li Chai

Comments Accepted by JMLR

Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance

Lisha Chen, Heshan Fernando, Yiming Ying, Tianyi Chen

Journal ref Journal of Machine Learning Research 25, no. 193 (2024): 1-53

Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding

Jiajing Zheng, Alexander D'Amour, Alexander Franks

Journal ref Journal of Machine Learning Research 26 (2025) 1-60

Enhancing Symbolic Regression with Quality-Diversity and Physics-Inspired Constraints

J. -P. Bruneton

Comments 23 pages, 1 figure, submitted to Journal of Machine Learning research

Sharp Analysis of Power Iteration for Tensor PCA

Yuchen Wu, Kangjie Zhou

Comments 42 pages, 11 figures, added additional experiments

Journal ref Journal of Machine Learning Research, 25(195):1-42, 2024

Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture Design

Lev Telyatnikov, Maria Sofia Bucarelli, Guillermo Bernardez, Olga Zaghen, Simone Scardapane, Pietro Lio

Comments This work has been published in Transactions on Machine Learning Research (TMLR). Please cite the journal version: https://openreview.net/forum?id=8rxtL0kZnX Link to bib: https://jmlr.org/tmlr/papers/bib/8rxtL0kZnX.bib

Journal ref Transactions on Machine Learning Research, 2025

Dropout Regularization Versus $\ell_2$-Penalization in the Linear Model

Gabriel Clara, Sophie Langer, Johannes Schmidt-Hieber

Comments 52 pages, 2 figures

Journal ref Journal of Machine Learning Research, 25(204), 2024

The Nyström method for convex loss functions

Andrea Della Vecchia, Ernesto De Vito, Jaouad Mourtada, Lorenzo Rosasco

Journal ref journal = {Journal of Machine Learning Research}, year = {2024}, volume = {25}, number = {360}, pages = {1--60}

Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training?

Shuxiao Chen, Qinqing Zheng, Qi Long, Weijie J. Su

Comments JMLR published version

Estimating network-mediated causal effects via principal components network regression

Alex Hayes, Mark M. Fredrickson, Keith Levin

Comments Updating to match published JMLR version

Journal ref Journal of Machine Learning Research 26 (2025): 1-99

Overparameterization of deep ResNet: zero loss and mean-field analysis

Zhiyan Ding, Shi Chen, Qin Li, Stephen Wright

Journal ref Journal of Machine Learning Research 23 (2022)

Langevin Monte Carlo: random coordinate descent and variance reduction

Zhiyan Ding, Qin Li

Comments arXiv admin note: text overlap with arXiv:2006.06068

Journal ref Journal of Machine Learning Research 22 (2021)

HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation

Weijie J. Su, Yuancheng Zhu

Comments Appeared in JMLR

Scaling ResNets in the Large-depth Regime

Pierre Marion, Adeline Fermanian, Gérard Biau, Jean-Philippe Vert

Comments 48 pages, 15 figures. Accepted to JMLR

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

Journal ref Journal of Machine Learning Research, 2025, vol. 25, no. 2, pp. 1-60

PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark

Jianqing Zhang, Yang Liu, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Jian Cao

Comments Accepted by JMLR

Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee

George H. Chen

Comments Journal of Machine Learning Research (JMLR 2024); this draft includes minor corrections over the original JMLR draft (main change: previously, the TUNA warm-start in Section 4 was inaccurately stated as to include an extra step of running a method by Chen (2020) but the final version of our code did not use this extra step--we updated Sections 4 and 5.2 and Appendices B and C.3 to match our code)

Random ReLU Neural Networks as Non-Gaussian Processes

Rahul Parhi, Pakshal Bohra, Ayoub El Biari, Mehrsa Pourya, Michael Unser

Journal ref Journal of Machine Learning Research, vol. 26, no. 19, pp. 1-31, 2025

Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets

Benjamin Dupuis, Paul Viallard, George Deligiannidis, Umut Simsekli

Journal ref Journal of Machine Learning Research (2024)

Random Forest Weighted Local Fréchet Regression with Random Objects

Rui Qiu, Zhou Yu, Ruoqing Zhu

Comments This paper has been published in the Journal of Machine Learning Research

Journal ref Journal of Machine Learning Research 25 (2024) 1-69

Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch

Shangtong Zhang, Remi Tachet, Romain Laroche

Comments Journal of Machine Learning Research 2022. This version improves the JMLR camera-ready version by removing all the projection operators in the algorithms

Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility

Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, François Caron

Comments 96 pages, 15 figures, 9 tables

Journal ref Journal Of Machine Learning Research, 24(289):1-78, 2023

Mean-Field Games With Finitely Many Players: Independent Learning and Subjectivity

Bora Yongacoglu, Gürdal Arslan, Serdar Yüksel

Comments Revised title. Accepted to the Journal of Machine Learning Research

Near-Optimal Algorithms for Making the Gradient Small in Stochastic Minimax Optimization

Lesi Chen, Luo Luo

Comments JMLR 2024

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

Comments 67 pages, 8 figures, to be published on Journal of Machine Learning Research (JMLR)

Building Efficient Lightweight CNN Models

Nathan Isong

Comments 25 pages, 22 figures, 6 tables, JMLR journal standard paper and to be submitted