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JMLR

Other ML
4,274 papers · 2000–2026

JMLR (Journal of Machine Learning Research) is a leading peer-reviewed journal covering all areas of machine learning.

Papers per year

4
73
118
118
252
309
2000
'5
'10
'15
'20
'25

Top authors

Michael I. Jordan 43 papers
Tong Zhang 30 papers
Martin J. Wainwright 25 papers
Francis Bach 22 papers
Peter L. Bartlett 21 papers
David B. Dunson 20 papers
Cynthia Rudin 19 papers
Chih-Jen Lin 19 papers
Peter Bühlmann 18 papers
Shai Shalev-shwartz 18 papers

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their counts at this venue are combined. How identity is handled.

Newest papers

Bridging Domain Invariance and Diversity: A Fine-Grained Risk Bound for Domain Generalization 2026
High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks 2026
Error Analyses of Auto-Regressive Video Diffusion Models 2026
Near-optimal Delta-convex Estimation of Lipschitz Functions 2026
The Sample Complexity of Parameter-Free Stochastic Convex Optimization 2026
End-to-End Deep Learning for Predicting Metric Space-Valued Outputs 2026
Graph-based Clustering Revisited: A Relaxation of Kernel k-Means Perspective 2026
Learning to Play Two-Player Perfect-Information Games without Knowledge 2026
Doubly Debiased Robust Subsampling for Transfer Learning 2026
Abstract Gradient Training: A Unified Certification Framework for Data Poisoning, Unlearning, and Differential Privacy 2026
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression 2026
Underdamped Langevin MCMC with third order convergence 2026
Approximation-Free Differentiable Oblique Decision Trees 2026
Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes 2026
Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes 2026
Robust training of implicit generative models for multivariate and heavy-tailed distributions with an invariant statistical loss 2026
Gradient Span Algorithms Make Predictable Progress in High Dimension 2026
py/cuTAGI: An Open-Source Library for Tractable Approximate Gaussian Inference in Bayesian Neural Networks 2026
Statistical Test for Attention in Transformers for Images and Time Series 2026
Accelerating Constrained Sampling: A Large Deviations Approach 2026
All JMLR 2026 papers →