JMLR

Entropic Fictitious Play for Mean Field Optimization Problem

Fan Chen, Zhenjie Ren, Songbo Wang

Comments 36 pages, 2 figures; version accepted by Journal of Machine Learning Research

Journal ref J.Mach.Learn.Res. 24(211) (2023) 1-36

Efficient computation of rankings from pairwise comparisons

M. E. J. Newman

Comments 25 pages, 1 figure, 1 table; additional material on MAP estimation and rates of convergence

Journal ref Journal of Machine Learning Research 24, 238 (2023)

Random Forests for Change Point Detection

Malte Londschien, Peter Bühlmann, Solt Kovács

Journal ref Journal of Machine Learning Research, 23(216):1-45, 2023

Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data

Vaidotas Simkus, Benjamin Rhodes, Michael U. Gutmann

Comments Published at Journal of Machine Learning Research (JMLR)

Journal ref Journal of Machine Learning Research, 24(196), 1-72, 2023

Clustering and Structural Robustness in Causal Diagrams

Santtu Tikka, Jouni Helske, Juha Karvanen

Comments This is the version published in JMLR

Journal ref Journal of Machine Learning Research, 24(195):1-32, 2023

Non-stationary Online Learning with Memory and Non-stochastic Control

Peng Zhao, Yu-Hu Yan, Yu-Xiang Wang, Zhi-Hua Zhou

Journal ref Journal of Machine Learning Research, 2023

MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks

Weicheng Kuo, AJ Piergiovanni, Dahun Kim, Xiyang Luo, Ben Caine, Wei Li, Abhijit Ogale, Luowei Zhou, Andrew Dai, Zhifeng Chen, Claire Cui, Anelia Angelova

Comments Published in Transactions on Machine Learning Research ( https://jmlr.org/tmlr/ ). 18 pages, 4 figures

Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity

Kaiqing Zhang, Sham M. Kakade, Tamer Başar, Lin F. Yang

Comments Updated version accepted to Journal of Machine Learning Research (JMLR)

Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence

Mattes Mollenhauer, Stefan Klus, Christof Schütte, Péter Koltai

Journal ref Journal of Machine Learning Research 23(327) 1-34, 2022

Factor Graph Neural Networks

Zhen Zhang, Mohammed Haroon Dupty, Fan Wu, Javen Qinfeng Shi, Wee Sun Lee

Comments Accepted by JMLR

Sparse Graph Learning from Spatiotemporal Time Series

Andrea Cini, Daniele Zambon, Cesare Alippi

Comments Accepted for publication in JMLR

Journal ref Journal of Machine Learning Research 24 (2023) 1-36

A Framework and Benchmark for Deep Batch Active Learning for Regression

David Holzmüller, Viktor Zaverkin, Johannes Kästner, Ingo Steinwart

Comments Published at the Journal of Machine Learning Research (JMLR). Changes in v4: Improvements in writing and other minor changes. Accompanying code can be found at https://github.com/dholzmueller/bmdal_reg

Journal ref Journal of Machine Learning Research, 24(164):1-81, 2023

Spectral learning of Bernoulli linear dynamical systems models

Iris R. Stone, Yotam Sagiv, Il Memming Park, Jonathan W. Pillow

Comments Published in Transactions on Machine Learning Research (https://jmlr.org/tmlr/papers/)

Journal ref Transactions on Machine Learning Research (2023)

Quantifying Network Similarity using Graph Cumulants

Gecia Bravo-Hermsdorff, Lee M. Gunderson, Pierre-André Maugis, Carey E. Priebe

Comments Shared first authorship. Title changed from "A principled (and practical) test for network comparison" to "Quantifying Network Similarity using Graph Cumulants". Updated version accepted for publication in Journal of Machine Learning Research (JMLR), 2023

Journal ref Journal of Machine Learning Research (JMLR), 2023

Weisfeiler and Leman go Machine Learning: The Story so far

Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten Borgwardt

Comments Accepted at JMLR

Towards Learning to Imitate from a Single Video Demonstration

Glen Berseth, Florian Golemo, Christopher Pal

Comments Published in JMLR. https://jmlr.org/papers/v24/21-1174.html

Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval

Yan Shuo Tan, Roman Vershynin

Journal ref Journal of Machine Learning Research, 24(58), 1-47 (2023)

F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning

Wenhao Li, Bo Jin, Xiangfeng Wang, Junchi Yan, Hongyuan Zha

Comments 75 pages, 10 figures, JMLR camera ready

Statistical Comparisons of Classifiers by Generalized Stochastic Dominance

Christoph Jansen, Malte Nalenz, Georg Schollmeyer, Thomas Augustin

Comments Accepted for publication in: Journal of Machine Learning Research (JMLR)

ReservoirComputing.jl: An Efficient and Modular Library for Reservoir Computing Models

Francesco Martinuzzi, Chris Rackauckas, Anas Abdelrehim, Miguel D. Mahecha, Karin Mora

Journal ref Journal of Machine Learning Research 23 (2022) 1-8

MultiZoo & MultiBench: A Standardized Toolkit for Multimodal Deep Learning

Paul Pu Liang, Yiwei Lyu, Xiang Fan, Arav Agarwal, Yun Cheng, Louis-Philippe Morency, Ruslan Salakhutdinov

Comments JMLR Open Source Software 2023, Code available at https://github.com/pliang279/MultiBench

Dimensionless machine learning: Imposing exact units equivariance

Soledad Villar, Weichi Yao, David W. Hogg, Ben Blum-Smith, Bianca Dumitrascu

Journal ref Journal of Machine Learning Research 24 (2023) 1--32

SMART: An Open Source Data Labeling Platform for Supervised Learning

Rob Chew, Michael Wenger, Caroline Kery, Jason Nance, Keith Richards, Emily Hadley, Peter Baumgartner

Comments 5 pages, 1 figure

Journal ref The Journal of Machine Learning Research, 20(1), 2999-3003 (2019)

Volterra Neural Networks (VNNs)

Siddharth Roheda, Hamid Krim

Comments Conference Version published in AAAI 2020. Journal version under review at JMLR

L0Learn: A Scalable Package for Sparse Learning using L0 Regularization

Hussein Hazimeh, Rahul Mazumder, Tim Nonet

Comments Accepted to JMLR (MLOSS)

A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning

Wei-Fang Sun, Cheng-Kuang Lee, Simon See, Chun-Yi Lee

Comments JMLR 2023. Extended version of arXiv:2102.07936

Graph Clustering with Graph Neural Networks

Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller

Comments JMLR 24(127) 1-21 2023

Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees

Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd

Comments 47 pages, 15 figures, and 5 tables. Accepted to JMLR

Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning

Titouan Vayer, Rémi Gribonval

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

A Parameter-Free Conditional Gradient Method for Composite Minimization under Hölder Condition

Masaru Ito, Zhaosong Lu, Chuan He

Comments 33 pages, 3 figures

Journal ref Journal of Machine Learning Research, Volume 24, No. 166, pp. 1-34, 2023