JMLR

Recursive Estimation of Conditional Kernel Mean Embeddings

Ambrus Tamás, Balázs Csanád Csáji

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

A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family

Trambak Banerjee, Qiang Liu, Gourab Mukherjee, Wenguang Sun

Journal ref Journal of Machine Learning Research 2021

Sensing Theorems for Unsupervised Learning in Linear Inverse Problems

Julián Tachella, Dongdong Chen, Mike Davies

Comments arXiv admin note: substantial text overlap with arXiv:2201.12151

Journal ref JMLR 2023

Optimization-based Causal Estimation from Heterogenous Environments

Mingzhang Yin, Yixin Wang, David M. Blei

Comments Journal of Machine Learning Research (JMLR). Code at https://github.com/mingzhang-yin/CoCo

Structured Optimal Variational Inference for Dynamic Latent Space Models

Peng Zhao, Anirban Bhattacharya, Debdeep Pati, Bani K. Mallick

Comments Accepted by the Journal of Machine Learning Research http://jmlr.org/papers/v25/22-0514.html

Concentration analysis of multivariate elliptic diffusion processes

Cathrine Aeckerle-Willems, Claudia Strauch, Lukas Trottner

Journal ref Journal of Machine Learning Research 24 (2023), paper no. 106, pp. 1-38

Just Wing It: Near-Optimal Estimation of Missing Mass in a Markovian Sequence

Ashwin Pananjady, Vidya Muthukumar, Andrew Thangaraj

Comments Version v2 simplifies proofs and corrects an error in Theorem 2. It is consistent with manuscript to appear in Journal of Machine Learning Research

Absolute State-wise Constrained Policy Optimization: High-Probability State-wise Constraints Satisfaction

Weiye Zhao, Feihan Li, Yifan Sun, Yujie Wang, Rui Chen, Tianhao Wei, Changliu Liu

Comments submission to Journal of Machine Learning Research

The loss landscape of deep linear neural networks: a second-order analysis

El Mehdi Achour, François Malgouyres, Sébastien Gerchinovitz

Journal ref Journal of Machine Learning Research, 2024, 25 (242), pp.1-76

The Multimarginal Optimal Transport Formulation of Adversarial Multiclass Classification

Nicolas Garcia Trillos, Matt Jacobs, Jakwang Kim

Journal ref Journal of Machine Learning Research 24(45), 2023, 1-56

Benchmarking Reliability of Deep Learning Models for Pathological Gait Classification

Abhishek Jaiswal, Nisheeth Srivastava

Comments 23 pages, Accepted in Machine Learning for Healthcare(MLHC) 2024, JMLR Volume 252

Journal ref JMLR Volume 252, year 2024

Fairness in Survival Analysis with Distributionally Robust Optimization

Shu Hu, George H. Chen

Comments Accepted at the Journal of Machine Learning Research; this paper is a journal paper extension of our earlier Machine Learning for Health 2022 paper (arXiv:2211.10508)

Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces

Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy

Journal ref Journal of Machine Learning Research, 2024

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

Comments 17 pages, 2 figures, JMLR MLOSS

Parallel-in-Time Probabilistic Numerical ODE Solvers

Nathanael Bosch, Adrien Corenflos, Fatemeh Yaghoobi, Filip Tronarp, Philipp Hennig, Simo Särkkä

Journal ref Journal of Machine Learning Research, 2024

On the Concentration of the Minimizers of Empirical Risks

Paul Escande

Journal ref Journal of Machine Learning Research, 2024, 25 (251), pp.1-53

Memory of recurrent networks: Do we compute it right?

Giovanni Ballarin, Lyudmila Grigoryeva, Juan-Pablo Ortega

Comments 33 pages, 6 figures

Journal ref Journal of Machine Learning Research, 25(243), 1-38 (2024)

White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?

Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma

Comments Accepted at Journal of Machine Learning Research. This paper integrates the works arXiv:2306.01129 and arXiv:2308.16271 into a complete story. In this paper, we improve the writing and organization, and also add conceptual, empirical, and theoretical improvements over the previous work. V2: small typo fixes/formatting improvements. V3: improvements from journal revisions. V4: fix figures

Pearl: A Production-ready Reinforcement Learning Agent

Zheqing Zhu, Rodrigo de Salvo Braz, Jalaj Bhandari, Daniel Jiang, Yi Wan, Yonathan Efroni, Liyuan Wang, Ruiyang Xu, Hongbo Guo, Alex Nikulkov, Dmytro Korenkevych, Urun Dogan, Frank Cheng, Zheng Wu, Wanqiao Xu

Journal ref Journal of Machine Learning Research, 2024

MLRegTest: A Benchmark for the Machine Learning of Regular Languages

Sam van der Poel, Dakotah Lambert, Kalina Kostyszyn, Tiantian Gao, Rahul Verma, Derek Andersen, Joanne Chau, Emily Peterson, Cody St. Clair, Paul Fodor, Chihiro Shibata, Jeffrey Heinz

Comments Accepted for publication in the Journal of Machine Learning Research. Dataset available at https://doi.org/10.5061/dryad.dncjsxm4h , code available at https://github.com/heinz-jeffrey/subregular-learning

On the Optimality of Misspecified Spectral Algorithms

Haobo Zhang, Yicheng Li, Qian Lin

Comments 50 pages, 2 figures

Journal ref Journal of Machine Learning Research,2024, volume 25,number 188, pages 1--50

Split Conformal Prediction and Non-Exchangeable Data

Roberto I. Oliveira, Paulo Orenstein, Thiago Ramos, João Vitor Romano

Journal ref Journal of Machine Learning Research, 25(225), 2024

PromptBench: A Unified Library for Evaluation of Large Language Models

Kaijie Zhu, Qinlin Zhao, Hao Chen, Jindong Wang, Xing Xie

Comments Accepted by Journal of Machine Learning Research (JMLR); code: https://github.com/microsoft/promptbench

Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression

Joseph Shenouda, Rahul Parhi, Kangwook Lee, Robert D. Nowak

Comments Updated to version published in JMLR

Journal ref Journal of Machine Learning Research, vol. 25, no. 231, pp. 1-40, 2024

Multi-Objective Neural Architecture Search by Learning Search Space Partitions

Yiyang Zhao, Linnan Wang, Tian Guo

Journal ref Journal of Machine Learning Research 25 (2024) 1-41

Improved Random Features for Dot Product Kernels

Jonas Wacker, Motonobu Kanagawa, Maurizio Filippone

Comments To appear in Journal of Machine Learning Research (JMLR)

Manifold Learning by Mixture Models of VAEs for Inverse Problems

Giovanni S. Alberti, Johannes Hertrich, Matteo Santacesaria, Silvia Sciutto

Journal ref Journal of Machine Learning Research, 25 (202), 1-35, 2024

Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm

Zhu Li, Dimitri Meunier, Mattes Mollenhauer, Arthur Gretton

Comments Published JMLR version. arXiv admin note: text overlap with arXiv:2208.01711

Pre-trained Gaussian Processes for Bayesian Optimization

Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani

Journal ref Journal of Machine Learning Research, 25(212):1-83, 2024. URL http://jmlr.org/papers/v25/23-0269.html

A Generalized Projected Bellman Error for Off-policy Value Estimation in Reinforcement Learning

Andrew Patterson, Adam White, Martha White

Comments Accepted for publication in JMLR 2022