JMLR

Euler Characteristic Tools For Topological Data Analysis

Olympio Hacquard, Vadim Lebovici

Comments 39 pages - Version accepted in JMLR

Journal ref Journal of Machine Learning Research 25 (2024) 1-39

Two is better than one: Regularized shrinkage of large minimum variance portfolio

Taras Bodnar, Nestor Parolya, Erik Thorsén

Comments 25 pages, 5 figures, 3 tables

Journal ref Journal of Machine Learning Research, 25(173), 2024, p. 1-32

Bayesian Regression Markets

Thomas Falconer, Jalal Kazempour, Pierre Pinson

Comments 35 pages, 11 figures, 3 tables. Published in Journal of Machine Learning Research (2024)

Fishnets: Information-Optimal, Scalable Aggregation for Sets and Graphs

T. Lucas Makinen, Justin Alsing, Benjamin D. Wandelt

Comments 15 pages, 6 figures, 2 tables. Submitted to JMLR

When Locally Linear Embedding Hits Boundary

Hau-tieng Wu, Nan Wu

Comments 70 Pages, 11 Figures

Journal ref Published in Journal of Machine Learning Research 24 (2023), 1-80

Sparse Projection Oblique Randomer Forests

Tyler M. Tomita, James Browne, Cencheng Shen, Jaewon Chung, Jesse L. Patsolic, Benjamin Falk, Jason Yim, Carey E. Priebe, Randal Burns, Mauro Maggioni, Joshua T. Vogelstein

Comments 31 pages; submitted to Journal of Machine Learning Research for review

Journal ref Journal of Machine Learning Research 21(104), 1-39, 2020

Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks

Fanghui Liu, Leello Dadi, Volkan Cevher

Comments Accepted by JMLR, update on the dimension dependence in sample complexity, see Prop. 5

Fixed points of nonnegative neural networks

Tomasz J. Piotrowski, Renato L. G. Cavalcante, Mateusz Gabor

Comments License: CC-BY 4.0, see https://creativecommons.org/licenses/by/4.0/. Attribution requirements are provided at http://jmlr.org/papers/v25/23-0167.html

Journal ref Journal of Machine Learning Research, 25(139):1-40, 2024

The Bayesian Learning Rule

Mohammad Emtiyaz Khan, Håvard Rue

Journal ref Journal of Machine Learning Research 24, no. 281 (2023): 1-46

Variational Estimators of the Degree-corrected Latent Block Model for Bipartite Networks

Yunpeng Zhao, Ning Hao, Ji Zhu

Journal ref Journal of Machine Learning Research 25 (2024) 1-42

DoWhy-GCM: An extension of DoWhy for causal inference in graphical causal models

Patrick Blöbaum, Peter Götz, Kailash Budhathoki, Atalanti A. Mastakouri, Dominik Janzing

Journal ref Journal of Machine Learning Research 25(147), 2024

Simple Cycle Reservoirs are Universal

Boyu Li, Robert Simon Fong, Peter Tiňo

Comments 28 pages

Journal ref Journal of Machine Learning Research 25 (2024) 1-28

Attraction-Repulsion Spectrum in Neighbor Embeddings

Jan Niklas Böhm, Philipp Berens, Dmitry Kobak

Journal ref JMLR 23(95):1-32, 2022

Optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization

Dmitry Kobak, Jonathan Lomond, Benoit Sanchez

Journal ref JMLR 21(169):1-16, 2020

More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity

Borja Rodríguez-Gálvez, Ragnar Thobaben, Mikael Skoglund

Comments 43 pages: ~20 of main text, ~6.5 of references, and ~17.5 of appendices. Published at JMLR

Nonparametric regression using over-parameterized shallow ReLU neural networks

Yunfei Yang, Ding-Xuan Zhou

Journal ref Journal of Machine Learning Research, 25(165):1-35, 2024

Neural Feature Learning in Function Space

Xiangxiang Xu, Lizhong Zheng

Comments 76 pages, 24 figures

Journal ref Journal of Machine Learning Research, Vol 25:142, 1-76, 2024

A survey on multi-player bandits

Etienne Boursier, Vianney Perchet

Comments final version, accepted at JMLR

Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations

Yuanyuan Wang, Wei Huang, Mingming Gong, Xi Geng, Tongliang Liu, Kun Zhang, Dacheng Tao

Journal ref Journal of Machine Learning Research 25 (2024) 1-50

PyGOD: A Python Library for Graph Outlier Detection

Kay Liu, Yingtong Dou, Xueying Ding, Xiyang Hu, Ruitong Zhang, Hao Peng, Lichao Sun, Philip S. Yu

Comments 9 pages, 1 figures. Published in JMLR Volume 25 MLOSS track. Library available at https://pygod.org

Journal ref Journal of Machine Learning Research. 25(141):1-9, 2024

Policy Trees for Prediction: Interpretable and Adaptive Model Selection for Machine Learning

Dimitris Bertsimas, Matthew Peroni

Comments Submitted to JMLR on 5/30/2024

Unsupervised anomaly detection algorithms on real-world data: how many do we need?

Roel Bouman, Zaharah Bukhsh, Tom Heskes

Comments The associated Git repository can be found at: https://github.com/RoelBouman/outlierdetection

Journal ref Journal of Machine Learning Research 25.105 (2024): 1-34

An Analysis of Quantile Temporal-Difference Learning

Mark Rowland, Rémi Munos, Mohammad Gheshlaghi Azar, Yunhao Tang, Georg Ostrovski, Anna Harutyunyan, Karl Tuyls, Marc G. Bellemare, Will Dabney

Comments Accepted to JMLR

Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria

Tengyuan Liang

Comments 27 pages, 2 figures

Journal ref Journal of Machine Learning Research 25 (2024) 1-27

Unified Binary and Multiclass Margin-Based Classification

Yutong Wang, Clayton Scott

Comments Accepted for publication in Journal of Machine Learning Research

OpenBox: A Python Toolkit for Generalized Black-box Optimization

Huaijun Jiang, Yu Shen, Yang Li, Beicheng Xu, Sixian Du, Wentao Zhang, Ce Zhang, Bin Cui

Journal ref Journal of Machine Learning Research 25.120 (2024): 1-11

Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality

Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy

Comments 49 pages, 1 figure. v2: revised asymptotic optimality results and reworked exposition. v3: minor updates

Journal ref Journal of Machine Learning Research, 25(90):1-49, 2024

Sum-of-norms clustering does not separate nearby balls

Alexander Dunlap, Jean-Christophe Mourrat

Comments 40 pages, 17 figures, published version

Journal ref Journal of Machine Learning Research, volume 25 (2024), no. 143, pp. 1--40

Finding Groups of Cross-Correlated Features in Bi-View Data

Miheer Dewaskar, John Palowitch, Mark He, Michael I. Love, Andrew B. Nobel

Comments 30 pages, 5 figures. R package: https://github.com/miheerdew/cbce

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

Kernel Thinning

Raaz Dwivedi, Lester Mackey

Comments Accepted for presentation as an extended abstract at the Conference on Learning Theory (COLT) 2021, and published in the Journal of Machine Learning Research (JMLR) 2024