JMLR

Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization

Tianyi Lin, Chi Jin, Michael. I. Jordan

Comments Accepted by Journal of Machine Learning Research; A preliminary version [arXiv:1906.00331] of this paper, with a subset of the results that are presented here, was presented at ICML 2020; 44 Pages, 10 Figures

Spectral Regularized Kernel Goodness-of-Fit Tests

Omar Hagrass, Bharath K. Sriperumbudur, Bing Li

Comments 49 pages. arXiv admin note: text overlap with arXiv:2212.09201

Journal ref Journal of Machine Learning Research, 25 (309): 1-52, 2024

Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents

Marco Pleines, Matthias Pallasch, Frank Zimmer, Mike Preuss

Comments 40 pages, 12 figures, 7 tables, accepted at JMLR

Enhancing Graph Representation Learning with Localized Topological Features

Zuoyu Yan, Qi Zhao, Ze Ye, Tengfei Ma, Liangcai Gao, Zhi Tang, Yusu Wang, Chao Chen

Comments Accepted in JMLR 2025

Optimal Scaling for the Proximal Langevin Algorithm in High Dimensions

Natesh S. Pillai

Comments 23 pages. arXiv admin note: substantial text overlap with arXiv:1103.0542

Journal ref Journal of Machine Learning Research, 2025

Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics

Noga Mudrik, Yenho Chen, Eva Yezerets, Christopher J. Rozell, Adam S. Charles

Comments 35 pages, 12 figures

Journal ref Journal of Machine Learning Research, 2024

On Doubly Robust Inference for Double Machine Learning in Semiparametric Regression

Oliver Dukes, Stijn Vansteelandt, David Whitney

Comments 46 pages, 9 figures

Journal ref Journal of Machine Learning Research, 2024

Gradual Domain Adaptation: Theory and Algorithms

Yifei He, Haoxiang Wang, Bo Li, Han Zhao

Comments JMLR camera-ready version. arXiv admin note: substantial text overlap with arXiv:2204.08200

Line Graph Vietoris-Rips Persistence Diagram for Topological Graph Representation Learning

Jaesun Shin, Eunjoo Jeon, Taewon Cho, Namkyeong Cho, Youngjune Gwon

Comments 36 pages. Accepted to Journal of Machine Learning Research

Learning Discretized Neural Networks under Ricci Flow

Jun Chen, Hanwen Chen, Mengmeng Wang, Guang Dai, Ivor W. Tsang, Yong Liu

Journal ref Journal of Machine Learning Research, 2024

Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach

Shuang Qiu, Boxiang Lyu, Qinglin Meng, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan

Comments Accepted in JMLR 2024

On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training

Chen Liu, Zhichao Huang, Mathieu Salzmann, Tong Zhang, Sabine Süsstrunk

Journal ref Journal of Machine Learning Research, Vol 25, 2024

Scaled Conjugate Gradient Method for Nonconvex Optimization in Deep Neural Networks

Naoki Sato, Koshiro Izumi, Hideaki Iiduka

Comments Accepted at JMLR (Dec. 2024)

GraphNeuralNetworks.jl: Deep Learning on Graphs with Julia

Carlo Lucibello, Aurora Rossi

Comments Submitted to JMLR OSS

A minimax optimal approach to high-dimensional double sparse linear regression

Yanhang Zhang, Zhifan Li, Shixiang Liu, Jianxin Yin

Comments 74 pages, 8 figures, 4 tables

Journal ref Journal of machine learning research, 2024

Memorization With Neural Nets: Going Beyond the Worst Case

Sjoerd Dirksen, Patrick Finke, Martin Genzel

Comments The current version of the manuscript has been accepted to Journal of Machine Learning Research

Journal ref J. Mach. Learn. Res. 25:347 (2024) 1-38

Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization

Huan Li, Zhouchen Lin

Comments Correct one typo in Algorithm 1: $\mathcal{N}_{(i)}$ -> $\mathcal{N}_{(i)}^k$

Journal ref Journal of Machine Learning Research (JMLR), 25(274):1-52, 2024

Stochastic subgradient for composite optimization with functional constraints

Ion Necoara, Nitesh Kumar Singh

Comments 32 pages, initial version July 2021, corrections November 2024

Journal ref Journal of Machine Learning Research, 2022

A Characterization of Multioutput Learnability

Vinod Raman, Unique Subedi, Ambuj Tewari

Comments 54 pages; JMLR version

Federated Automatic Differentiation

Keith Rush, Zachary Charles, Zachary Garrett

Comments 39 pages, 13 figures. To appear in JMLR 25 (2024)

Optimistic search: Change point estimation for large-scale data via adaptive logarithmic queries

Solt Kovács, Housen Li, Lorenz Haubner, Axel Munk, Peter Bühlmann

Comments Generalize the univariate theory to Gaussian mean changes of general dimension, including high-dimensional scenarios

Journal ref Journal of Machine Learning Research, 25(297): 1-64, 2024

Operator learning without the adjoint

Nicolas Boullé, Diana Halikias, Samuel E. Otto, Alex Townsend

Comments 54 pages, 5 figures, to appear in Journal of Machine Learning Research

Generalization on the Unseen, Logic Reasoning and Degree Curriculum

Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Kevin Rizk

Comments extended JMLR version of the original ICML 2023 paper

PAPAL: A Provable PArticle-based Primal-Dual ALgorithm for Mixed Nash Equilibrium

Shihong Ding, Hanze Dong, Cong Fang, Zhouchen Lin, Tong Zhang

Comments Published in Journal of Machine Learning Research 25 (2024) 1-48

Towards Explainable Evaluation Metrics for Machine Translation

Christoph Leiter, Piyawat Lertvittayakumjorn, Marina Fomicheva, Wei Zhao, Yang Gao, Steffen Eger

Comments Published at JMLR 3/24. We released an earlier preprint of this paper under a different title (arXiv:2203.11131)

Journal ref Journal of Machine Learning Research (JMLR), 2024, vol. 25, no. 75, p. 1-49

Open-Source Conversational AI with SpeechBrain 1.0

Mirco Ravanelli, Titouan Parcollet, Adel Moumen, Sylvain de Langen, Cem Subakan, Peter Plantinga, Yingzhi Wang, Pooneh Mousavi, Luca Della Libera, Artem Ploujnikov, Francesco Paissan, Davide Borra, Salah Zaiem, Zeyu Zhao, Shucong Zhang, Georgios Karakasidis, Sung-Lin Yeh, Pierre Champion, Aku Rouhe, Rudolf Braun, Florian Mai, Juan Zuluaga-Gomez, Seyed Mahed Mousavi, Andreas Nautsch, Ha Nguyen, Xuechen Liu, Sangeet Sagar, Jarod Duret, Salima Mdhaffar, Gaelle Laperriere, Mickael Rouvier, Renato De Mori, Yannick Esteve

Comments Accepted to the Journal of Machine Learning research (JMLR), Machine Learning Open Source Software

Empirical Design in Reinforcement Learning

Andrew Patterson, Samuel Neumann, Martha White, Adam White

Comments Published in JMLR 2024

Towards An Efficient Approach for the Nonconvex $\ell_p$ Ball Projection: Algorithm and Analysis

Xiangyu Yang, Jiashan Wang, Hao Wang

Comments This paper has already been accepted by the Journal of Machine Learning Research

A Rainbow in Deep Network Black Boxes

Florentin Guth, Brice Ménard, Gaspar Rochette, Stéphane Mallat

Comments 59 pages, 10 figures. To appear at JMLR

On the Convexity and Reliability of the Bethe Free Energy Approximation

Harald Leisenberger, Christian Knoll, Franz Pernkopf

Comments This work has been submitted to the Journal of Machine Learning Research (JMLR) for possible publication