JMLR

Modular Regression: Improving Linear Models by Incorporating Auxiliary Data

Ying Jin, Dominik Rothenhäusler

Comments Journal of Machine Learning Research

Community Recovery in the Geometric Block Model

Sainyam Galhotra, Arya Mazumdar, Soumyabrata Pal, Barna Saha

Comments 53 pages, 18 figures. Accepted at the Journal of Machine Learning Research (JMLR). Shorter versions accepted in AAAI 2018 (see arXiv:1709.05510) and RANDOM 2019 (see arXiv:1804.05013). arXiv admin note: text overlap with arXiv:1804.05013

Journal ref Journal of Machine Learning Research (JMLR) 2023

AMLB: an AutoML Benchmark

Pieter Gijsbers, Marcos L. P. Bueno, Stefan Coors, Erin LeDell, Sébastien Poirier, Janek Thomas, Bernd Bischl, Joaquin Vanschoren

Comments UNDER REVIEW: Revised submission to JMLR, with updated results from June 2023

Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-start

Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo

Comments Corrected Remark 18 + other small edits. Code at https://github.com/CSML-IIT-UCL/bioptexps

Journal ref Journal of Machine Learning Research, volume 24, number 167, pages 1-37, year 2023

Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach

Dimitris Bertsimas, Ryan Cory-Wright, Nicholas A. G. Johnson

Journal ref Journal of Machine Learning Research, 24(267), 1-51 (2023)

Instance-Dependent Generalization Bounds via Optimal Transport

Songyan Hou, Parnian Kassraie, Anastasis Kratsios, Andreas Krause, Jonas Rothfuss

Comments Journal of Machine Learning Research (JMLR), 51 pages

Incremental Learning in Diagonal Linear Networks

Raphaël Berthier

Journal ref Journal of Machine Learning Research, 2023, 24 (171), pp.1-26

RankSEG: A Consistent Ranking-based Framework for Segmentation

Ben Dai, Chunlin Li

Comments 50 pages

Journal ref Journal of Machine Learning Research, 24(224), 1-50 (2023)

Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms

Haoxiang Wang, Gargi Balasubramaniam, Haozhe Si, Bo Li, Han Zhao

Comments Submitted to JMLR. This journal version significantly extends our ICML 2022 paper, arXiv:2201.12919

A Continuous-time Stochastic Gradient Descent Method for Continuous Data

Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb

Journal ref Journal of Machine Learning Research 24(274), pp. 1-48, 2023

Elastic Gradient Descent, an Iterative Optimization Method Approximating the Solution Paths of the Elastic Net

Oskar Allerbo, Johan Jonasson, Rebecka Jörnsten

Journal ref Journal of Machine Learning Research 24 (2023) 1-53

Small Transformers Compute Universal Metric Embeddings

Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanić

Comments 42 pages, 10 Figures, 3 Tables

Journal ref Journal of Machine Learning Research 24 (2023): 1-48

Approximation algorithms for stochastic clustering

David G. Harris, Shi Li, Thomas Pensyl, Aravind Srinivasan, Khoa Trinh

Comments The version of this paper published in JMLR is incorrect; specifically, Theorem 14 of that paper appears to be fatally flawed. The version posted here on arxiv removes the claimed incorrect results

Journal ref Journal of Machine Learning Research 20(153), pp. 1-33 (2019)

Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching

Eliezer de Souza da Silva, Tomasz Kuśmierczyk, Marcelo Hartmann, Arto Klami

Journal ref Journal of Machine Learning Research 24 (2023) 1-51

On Regularized Square-root Regression Problems: Distributionally Robust Interpretation and Fast Computations

Hong T. M. Chu, Kim-Chuan Toh, Yangjing Zhang

Comments 39 pages, 7 figures

Journal ref Journal of Machine Learning Research, 23 (2022), pp 1-39

Distributed nonparametric regression imputation for missing response problems with large-scale data

Ruoyu Wang, Miaomiao Su, Qihua Wang

Journal ref Journal of Machine Learning Research, 2023

Interpretable and Fair Boolean Rule Sets via Column Generation

Connor Lawless, Sanjeeb Dash, Oktay Gunluk, Dennis Wei

Comments arXiv admin note: substantial text overlap with arXiv:2107.01325, arXiv:1805.09901

Journal ref Journal of Machine Learning Research 2023 Volume 24, Number 229, Pages 1-50

Torchhd: An Open Source Python Library to Support Research on Hyperdimensional Computing and Vector Symbolic Architectures

Mike Heddes, Igor Nunes, Pere Vergés, Denis Kleyko, Danny Abraham, Tony Givargis, Alexandru Nicolau, Alexander Veidenbaum

Journal ref Journal of Machine Learning Research 24 (2023) 1--10

Random Feature Amplification: Feature Learning and Generalization in Neural Networks

Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett

Comments 46 pages; JMLR camera ready revision

MKL-$L_{0/1}$-SVM

Bin Zhu, Yijie Shi

Comments 26 pages in the JMLR template, 3 figures, and 2 tables, submitted to the Journal of Machine Learning Research, with minor text overlap with arXiv: 2303.04445 (conference version). arXiv admin note: text overlap with arXiv:2303.04445

Combinatorial optimization and reasoning with graph neural networks

Quentin Cappart, Didier Chételat, Elias Khalil, Andrea Lodi, Christopher Morris, Petar Veličković

Journal ref Journal of Machine Learning Research, 24(130):1-61, 2023

On Low-rank Trace Regression under General Sampling Distribution

Nima Hamidi, Mohsen Bayati

Comments 49 pages, 6 figure2

Journal ref Journal of Machine Learning Research (JMLR), 2022

The Measure and Mismeasure of Fairness

Sam Corbett-Davies, Johann D. Gaebler, Hamed Nilforoshan, Ravi Shroff, Sharad Goel

Journal ref Journal of Machine Learning Research, Vol. 24, 2023

An Empirical Investigation of the Role of Pre-training in Lifelong Learning

Sanket Vaibhav Mehta, Darshan Patil, Sarath Chandar, Emma Strubell

Journal ref Journal of Machine Learning Research 24 (2023) 1-50

Variational Inference for Deblending Crowded Starfields

Runjing Liu, Jon D. McAuliffe, Jeffrey Regier

Journal ref Journal of Machine Learning Research, volume 24, 2023

On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators

Zejian Liu, Meng Li

Comments Accepted by Journal of Machine Learning Research

Improving multiple-try Metropolis with local balancing

Philippe Gagnon, Florian Maire, Giacomo Zanella

Journal ref Journal of Machine Learning Research, 24(248), 1-59 (2023)

Individual Fairness in Hindsight

Swati Gupta, Vijay Kamble

Journal ref Journal of Machine Learning Research, 2021

Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications

Marcel Wienöbst, Max Bannach, Maciej Liśkiewicz

Comments arXiv admin note: text overlap with arXiv:2012.09679

Journal ref Journal of Machine Learning Research 24(213):1-45, 2023

MMD Aggregated Two-Sample Test

Antonin Schrab, Ilmun Kim, Mélisande Albert, Béatrice Laurent, Benjamin Guedj, Arthur Gretton

Comments 81 pages

Journal ref Journal of Machine Learning Research 24(194), 1-81, 2023