JMLR

Selection by Prediction with Conformal p-values

Ying Jin, Emmanuel J. Candès

Comments Journal of Machine Learning Research

Stochastic Optimization under Distributional Drift

Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui

Comments 56 pages, 7 figures. v2: unified analysis of time- and decision-dependent settings; updated numerical experiments. v3: added references and updated exposition. v4: minor updates to match the version published in JMLR

Journal ref Journal of Machine Learning Research, 24(147):1-56, 2023

A universally consistent learning rule with a universally monotone error

Vladimir Pestov

Comments latex, 27 pp., 4 figures, to appear in JMLR. The version, reformatted in the JMLR style, incorporates a number of remarks by two anonymous referees that have helped to fix some confusing passages and make the paper more readable

Journal ref Journal of Machine Learning Research 23 (2022), Paper No. 157, 27 pp

Asymptotics of Network Embeddings Learned via Subsampling

Andrew Davison, Morgane Austern

Comments Accepted at Journal of Machine Learning Research (JMLR). 120 pages, 3 figures, 1 table

Journal ref Journal of Machine Learning Research 24 (2023) 1-120. Published 5/23

Fast and Robust Rank Aggregation against Model Misspecification

Yuangang Pan, Weijie Chen, Gang Niu, Ivor W. Tsang, Masashi Sugiyama

Comments https://github.com/Numb3rs-UTS/Robust-Ranking-Aggregation--CoarsenRank

Journal ref Journal of Machine Learning Research, 2022, 23(23):1-35

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond

Anna Hedström, Leander Weber, Dilyara Bareeva, Daniel Krakowczyk, Franz Motzkus, Wojciech Samek, Sebastian Lapuschkin, Marina M. -C. Höhne

Comments 4 pages, 1 figure, 1 table

Journal ref Journal of Machine Learning Research, Vol. 24 (2023) 1-11

Maximum Likelihood Estimation in Gaussian Process Regression is Ill-Posed

Toni Karvonen, Chris J. Oates

Comments An important work is missing from our literature review. Ben Salem, Bachoc, Roustant, Gamboa and Tomaso [Gaussian process-based dimension reduction for goal-oriented sequential design. SIAM/ASA Journal on Uncertainty Quantification, 7(4):1369-1397, 2019. See Proposition 4.3.] have proved parts of Theorems 2.3 and 5.3 using a technique that is more or less identical to the proof in Section 7.4

Journal ref Journal of Machine Learning Research, 24(120):1-47, 2023

An Analysis of Robustness of Non-Lipschitz Networks

Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang

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

Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Condition

Zhishuai Guo, Yan Yan, Zhuoning Yuan, Tianbao Yang

Comments Accepted by Journal of Machine Learning Research

Tree-AMP: Compositional Inference with Tree Approximate Message Passing

Antoine Baker, Benjamin Aubin, Florent Krzakala, Lenka Zdeborová

Comments Source code available at https://github.com/sphinxteam/tramp and documentation at https://sphinxteam.github.io/tramp.docs

Journal ref Journal of Machine Learning Research 24 (2023) 1-89

The Implicit Bias of Benign Overfitting

Ohad Shamir

Comments Version published in the Journal of Machine Learning Research

Journal ref JMLR 24(113):1-40, 2023

Flexible Model Aggregation for Quantile Regression

Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani

Comments Accepted at JMLR 2023

Off-Policy Actor-Critic with Emphatic Weightings

Eric Graves, Ehsan Imani, Raksha Kumaraswamy, Martha White

Comments 63 pages

Journal ref Journal of Machine Learning Research 24 (2023) 1-63

Copula Correlation: An Equitable Dependence Measure and Extension of Pearson's Correlation

A. Adam Ding, Yi Li

Journal ref The Journal of Machine Learning Research 2017

Temporal Abstraction in Reinforcement Learning with the Successor Representation

Marlos C. Machado, Andre Barreto, Doina Precup, Michael Bowling

Comments This is the final, published JMLR version

Journal ref Journal of Machine Learning Research (JMLR), 24(80):1-69, 2023

Fast Online Changepoint Detection via Functional Pruning CUSUM statistics

Gaetano Romano, Idris Eckley, Paul Fearnhead, Guillem Rigaill

Journal ref Journal of Machine Learning Research, 2023

Monotonic Alpha-divergence Minimisation for Variational Inference

Kamélia Daudel, Randal Douc, François Roueff

Journal ref Journal of Machine Learning Research, 24(62):1-76, 2023

Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces

George Stepaniants

Comments 72 pages, 10 figures

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

Fundamental limits and algorithms for sparse linear regression with sublinear sparsity

Lan V. Truong

Comments Journal of Machine Learning Research (JMLR), 24(64):1-49, 2023

On the Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size

Xiaoyu Wang, Ya-xiang Yuan

Journal ref Journal of Machine Learning Research.24(2023)1-49

On the Complexity of SHAP-Score-Based Explanations: Tractability via Knowledge Compilation and Non-Approximability Results

Marcelo Arenas, Pablo Barceló, Leopoldo Bertossi, Mikaël Monet

Comments Up to the formatting, this is the exact content of the paper in Journal of Machine Learning Research (JMLR)

Necessary and Sufficient Conditions for Inverse Reinforcement Learning of Bayesian Stopping Time Problems

Kunal Pattanayak, Vikram Krishnamurthy

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

Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities

Brian R. Bartoldson, Bhavya Kailkhura, Davis Blalock

Comments 77 pages

Journal ref Journal of Machine Learning Research (2023)

Inference for a Large Directed Acyclic Graph with Unspecified Interventions

Chunlin Li, Xiaotong Shen, Wei Pan

Comments 48 pages, 13 figures

Journal ref Journal of Machine Learning Research, 2023

IDMS: Instance Depth for Multi-scale Monocular 3D Object Detection

Chao Hu, Liqiang Zhu, Weibing Qiu, Weijie Wu

Comments This submission has been withdrawn by arXiv administrators due to inappropriate text overlap with external sources

Journal ref Journal of Machine Learning Research 2023

First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems

Michael I. Jordan, Tianyi Lin, Manolis Zampetakis

Comments Accepted by Journal of Machine Learning Research; Add the references and the funding information; 44 pages, 1 table

Communication-Efficient Learning of Deep Networks from Decentralized Data

H. Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, Blaise Agüera y Arcas

Comments [v4] Fixes a typo in the FedAvg pseudocode. [v3] Updates the large-scale LSTM experiments, along with other minor changes

Journal ref Proceedings of the 20 th International Conference on Artificial Intelligence and Statistics (AISTATS) 2017. JMLR: W&CP volume 54

Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions

Jon Vadillo, Roberto Santana, Jose A. Lozano

Comments Final version as accepted in JMLR. Attribution requirements are provided at http://jmlr.org/papers/v24/21-0326.html

Journal ref Journal of Machine Learning Research, 24(15):1-42, 2023

Three rates of convergence or separation via U-statistics in a dependent framework

Quentin Duchemin, Yohann De Castro, Claire Lacour

Comments arXiv admin note: substantial text overlap with arXiv:2011.11435

Journal ref Journal of Machine Learning Research 23 (2022) 1-59

HiClass: a Python library for local hierarchical classification compatible with scikit-learn

Fábio M. Miranda, Niklas Köhnecke, Bernhard Y. Renard

Comments 17 pages, 9 figures, 7 tables

Journal ref Journal of Machine Learning Research 24 (2023) 1-17