Journal of Machine Learning Research

The Journal of Machine Learning Research (JMLR), established in 2000, 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.

News

• 2023.01.20: Volume 23 completed; Volume 24 began.
• 2022.07.20: New special issue on climate change.
• 2022.02.18: New blog post: Retrospectives from 20 Years of JMLR .
• 2022.01.25: Volume 22 completed; Volume 23 began.
• 2021.12.02: Message from outgoing co-EiC Bernhard Schölkopf.
• 2021.02.10: Volume 21 completed; Volume 22 began.
• More news ...

Latest papers

• The d-Separation Criterion in Categorical Probability

  Tobias Fritz, Andreas Klingler, 2023

• The multimarginal optimal transport formulation of adversarial multiclass classification

  Nicolás García Trillos, Matt Jacobs, Jakwang Kim, 2023

• Robust Load Balancing with Machine Learned Advice

  Sara Ahmadian, Hossein Esfandiari, Vahab Mirrokni, Binghui Peng, 2023

• Benchmarking Graph Neural Networks

  Vijay Prakash Dwivedi, Chaitanya K. Joshi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson, 2023

• A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness

  Jeremiah Zhe Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan, 2023

• Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data

  Shaowu Pan, Steven L. Brunton, J. Nathan Kutz, 2023

• On Batch Teaching Without Collusion

  Shaun Fallat, David Kirkpatrick, Hans U. Simon, Abolghasem Soltani, Sandra Zilles, 2023

• Sensing Theorems for Unsupervised Learning in Linear Inverse Problems

  Julián Tachella, Dongdong Chen, Mike Davies, 2023

• First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems

  Michael I. Jordan, Tianyi Lin, Manolis Zampetakis, 2023

• Ridges, Neural Networks, and the Radon Transform

  Michael Unser, 2023

• Label Distribution Changing Learning with Sample Space Expanding

  Chao Xu, Hong Tao, Jing Zhang, Dewen Hu, Chenping Hou, 2023

• Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers?

  Han Zhong, Zhuoran Yang, Zhaoran Wang, Michael I. Jordan, 2023

• Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond

  Anna Hedström, Leander Weber, Daniel Krakowczyk, Dilyara Bareeva, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne, 2023

• Gap Minimization for Knowledge Sharing and Transfer

  Boyu Wang, Jorge A. Mendez, Changjian Shui, Fan Zhou, Di Wu, Gezheng Xu, Christian Gagné, Eric Eaton, 2023

• Sparse PCA: a Geometric Approach

  Dimitris Bertsimas, Driss Lahlou Kitane, 2023

• Labels, Information, and Computation: Efficient Learning Using Sufficient Labels

  Shiyu Duan, Spencer Chang, Jose C. Principe, 2023

• Attacks against Federated Learning Defense Systems and their Mitigation

  Cody Lewis, Vijay Varadharajan, Nasimul Noman, 2023

• HiClass: a Python Library for Local Hierarchical Classification Compatible with Scikit-learn

  Fábio M. Miranda, Niklas Köhnecke, Bernhard Y. Renard, 2023

• Impact of classification difficulty on the weight matrices spectra in Deep Learning and application to early-stopping

  XuranMeng, JeffYao, 2023

• The SKIM-FA Kernel: High-Dimensional Variable Selection and Nonlinear Interaction Discovery in Linear Time

  Raj Agrawal, Tamara Broderick, 2023

• Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels

  Hao Wang, Rui Gao, Flavio P. Calmon, 2023

• Discrete Variational Calculus for Accelerated Optimization

  Cédric M. Campos, Alejandro Mahillo, David Martín de Diego, 2023

• Calibrated Multiple-Output Quantile Regression with Representation Learning

  Shai Feldman, Stephen Bates, Yaniv Romano, 2023

• Bayesian Data Selection

  Eli N. Weinstein, Jeffrey W. Miller, 2023

• Lower Bounds and Accelerated Algorithms for Bilevel Optimization

  Kaiyi ji, Yingbin Liang, 2023

• Graph-Aided Online Multi-Kernel Learning

  Pouya M. Ghari, Yanning Shen, 2023

• Interpolating Classifiers Make Few Mistakes

  Tengyuan Liang, Benjamin Recht, 2023

• Regularized Joint Mixture Models

  Konstantinos Perrakis, Thomas Lartigue, Frank Dondelinger, Sach Mukherjee, 2023

• An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization

  Le Thi Khanh Hien, Duy Nhat Phan, Nicolas Gillis, 2023

• Learning Mean-Field Games with Discounted and Average Costs

  Berkay Anahtarci, Can Deha Kariksiz, Naci Saldi, 2023

• Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation

  Cynthia Rudin, Yaron Shaposhnik, 2023

• Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions

  Jon Vadillo, Roberto Santana, Jose A. Lozano, 2023

• Python package for causal discovery based on LiNGAM

  Takashi Ikeuchi, Mayumi Ide, Yan Zeng, Takashi Nicholas Maeda, Shohei Shimizu, 2023

• Adaptation to the Range in K-Armed Bandits

  Hédi Hadiji, Gilles Stoltz, 2023

• Learning-augmented count-min sketches via Bayesian nonparametrics

  Emanuele Dolera, Stefano Favaro, Stefano Peluchetti, 2023

• Optimal Strategies for Reject Option Classifiers

  Vojtech Franc, Daniel Prusa, Vaclav Voracek, 2023

• A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees

  Michael J. O'Neill, Stephen J. Wright, 2023

• Sampling random graph homomorphisms and applications to network data analysis

  Hanbaek Lyu, Facundo Memoli, David Sivakoff, 2023

• A Relaxed Inertial Forward-Backward-Forward Algorithm for Solving Monotone Inclusions with Application to GANs

  Radu I. Bot, Michael Sedlmayer, Phan Tu Vuong, 2023

• On Distance and Kernel Measures of Conditional Dependence

  Tianhong Sheng, Bharath K. Sriperumbudur, 2023

• AutoKeras: An AutoML Library for Deep Learning

  Haifeng Jin, François Chollet, Qingquan Song, Xia Hu, 2023

• Cluster-Specific Predictions with Multi-Task Gaussian Processes

  Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey, 2023

• Efficient Structure-preserving Support Tensor Train Machine

  Kirandeep Kour, Sergey Dolgov, Martin Stoll, Peter Benner, 2023

• Bayesian Spiked Laplacian Graphs

  Leo L Duan, George Michailidis, Mingzhou Ding, 2023

• The Brier Score under Administrative Censoring: Problems and a Solution

  Håvard Kvamme, Ørnulf Borgan, 2023

• Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search

  Benjamin Moseley, Joshua R. Wang, 2023

• See more