J. Mach. Learn. Res.

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Publications

volume 24, 2023

Hengrui Cai, Chengchun Shi, Rui Song, Wenbin Lu
Jump Interval-Learning for Individualized Decision Making with Continuous Treatments. J. Mach. Learn. Res. 24 (2023)
Hui Jin, Guido Montúfar
Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks. J. Mach. Learn. Res. 24 (2023)
Ibrahim Merad, Stéphane Gaïffas
Robust Methods for High-Dimensional Linear Learning. J. Mach. Learn. Res. 24 (2023)
Dimitris Bertsimas, Driss Lahlou Kitane
Sparse PCA: a Geometric Approach. J. Mach. Learn. Res. 24 (2023)
Michael Unser
Ridges, Neural Networks, and the Radon Transform. J. Mach. Learn. Res. 24 (2023)
Lingjun Li, Jun Li
Online Change-Point Detection in High-Dimensional Covariance Structure with Application to Dynamic Networks. J. Mach. Learn. Res. 24 (2023)
Changhoon Song, Geonho Hwang, Junho Lee, Myungjoo Kang
Minimal Width for Universal Property of Deep RNN. J. Mach. Learn. Res. 24 (2023)
Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller
Graph Clustering with Graph Neural Networks. J. Mach. Learn. Res. 24 (2023)
Tobias Fritz, Andreas Klingler
The d-Separation Criterion in Categorical Probability. J. Mach. Learn. Res. 24 (2023)
Marlos C. Machado, André Barreto, Doina Precup, Michael Bowling
Temporal Abstraction in Reinforcement Learning with the Successor Representation. J. Mach. Learn. Res. 24 (2023)
Abhishek Kaul, Hongjin Zhang, Konstantinos Tsampourakis, George Michailidis
Inference on the Change Point under a High Dimensional Covariance Shift. J. Mach. Learn. Res. 24 (2023)
Chen Lu, Subhabrata Sen
Contextual Stochastic Block Model: Sharp Thresholds and Contiguity. J. Mach. Learn. Res. 24 (2023)
Shuang Zhou, Debdeep Pati, Tianying Wang, Yun Yang, Raymond J. Carroll
Gaussian Processes with Errors in Variables: Theory and Computation. J. Mach. Learn. Res. 24 (2023)
Pouya M. Ghari, Yanning Shen
Graph-Aided Online Multi-Kernel Learning. J. Mach. Learn. Res. 24 (2023)
Giora Simchoni, Saharon Rosset
Integrating Random Effects in Deep Neural Networks. J. Mach. Learn. Res. 24 (2023)
Hau-Tieng Wu, Nan Wu
When Locally Linear Embedding Hits Boundary. J. Mach. Learn. Res. 24 (2023)
Martijn Gösgens, Remco van der Hofstad, Nelly Litvak
The Hyperspherical Geometry of Community Detection: Modularity as a Distance. J. Mach. Learn. Res. 24 (2023)
Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees. J. Mach. Learn. Res. 24 (2023)
Eric Graves, Ehsan Imani, Raksha Kumaraswamy, Martha White
Off-Policy Actor-Critic with Emphatic Weightings. J. Mach. Learn. Res. 24 (2023)
Eli N. Weinstein, Jeffrey W. Miller
Bayesian Data Selection. J. Mach. Learn. Res. 24 (2023)
Andrew Davison, Morgane Austern
Asymptotics of Network Embeddings Learned via Subsampling. J. Mach. Learn. Res. 24 (2023)
Zhishuai Guo, Yan Yan, Zhuoning Yuan, Tianbao Yang
Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Condition. J. Mach. Learn. Res. 24 (2023)
Fábio Malcher Miranda, Niklas Köhnecke, Bernhard Y. Renard
HiClass: a Python Library for Local Hierarchical Classification Compatible with Scikit-learn. J. Mach. Learn. Res. 24 (2023)
Gaetano Romano, Idris A. Eckley, Paul Fearnhead, Guillem Rigaill
Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics. J. Mach. Learn. Res. 24 (2023)
Xi Wang, Zhipeng Tu, Yiguang Hong, Yingyi Wu, Guodong Shi
Online Optimization over Riemannian Manifolds. J. Mach. Learn. Res. 24 (2023)
Qinbo Bai, Vaneet Aggarwal, Ather Gattami
Provably Sample-Efficient Model-Free Algorithm for MDPs with Peak Constraints. J. Mach. Learn. Res. 24 (2023)
Hamid Reza Feyzmahdavian, Mikael Johansson
Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees. J. Mach. Learn. Res. 24 (2023)
Johannes Resin
From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions. J. Mach. Learn. Res. 24 (2023)
Manoj Kumar, Anurag Sharma, Sandeep Kumar
A Unified Framework for Optimization-Based Graph Coarsening. J. Mach. Learn. Res. 24 (2023)
Konstantinos Perrakis, Thomas Lartigue, Frank Dondelinger, Sach Mukherjee
Regularized Joint Mixture Models. J. Mach. Learn. Res. 24 (2023)
Ning Ning, Edward L. Ionides
Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality. J. Mach. Learn. Res. 24 (2023)
Anastasis Kratsios, Valentin Debarnot, Ivan Dokmanic
Small Transformers Compute Universal Metric Embeddings. J. Mach. Learn. Res. 24 (2023)
Berkay Anahtarci, Can Deha Kariksiz, Naci Saldi
Learning Mean-Field Games with Discounted and Average Costs. J. Mach. Learn. Res. 24 (2023)
Ohad Shamir
The Implicit Bias of Benign Overfitting. J. Mach. Learn. Res. 24 (2023)
Eliezer de Souza da Silva, Tomasz Kusmierczyk, Marcelo Hartmann, Arto Klami
Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching. J. Mach. Learn. Res. 24 (2023)
Yuqi Gu, Elena E. Erosheva, Gongjun Xu, David B. Dunson
Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data. J. Mach. Learn. Res. 24 (2023)
Nicolás García Trillos, Pengfei He, Chenghui Li
Large sample spectral analysis of graph-based multi-manifold clustering. J. Mach. Learn. Res. 24 (2023)
Snigdha Panigrahi, Peter W. MacDonald, Daniel Kessler
Approximate Post-Selective Inference for Regression with the Group LASSO. J. Mach. Learn. Res. 24 (2023)
William J. Wilkinson, Simo Särkkä, Arno Solin
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees. J. Mach. Learn. Res. 24 (2023)
Dun Zeng, Siqi Liang, Xiangjing Hu, Hui Wang, Zenglin Xu
FedLab: A Flexible Federated Learning Framework. J. Mach. Learn. Res. 24 (2023)
Shoaib Bin Masud, Matthew Werenski, James M. Murphy, Shuchin Aeron
Multivariate Soft Rank via Entropy-Regularized Optimal Transport: Sample Efficiency and Generative Modeling. J. Mach. Learn. Res. 24 (2023)
Cédric M. Campos, Alejandro Mahillo, David Martín de Diego
Discrete Variational Calculus for Accelerated Optimization. J. Mach. Learn. Res. 24 (2023)
Yunxiao Chen, Chengcheng Li, Jing Ouyang, Gongjun Xu
Statistical Inference for Noisy Incomplete Binary Matrix. J. Mach. Learn. Res. 24 (2023)
Xu Han, Xiaohui Chen, Francisco J. R. Ruiz, Li-Ping Liu
Fitting Autoregressive Graph Generative Models through Maximum Likelihood Estimation. J. Mach. Learn. Res. 24 (2023)
Kirthevasan Kandasamy, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica
VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback. J. Mach. Learn. Res. 24 (2023)
Cheng Zeng, Jeffrey W. Miller, Leo L. Duan
Consistent Model-based Clustering using the Quasi-Bernoulli Stick-breaking Process. J. Mach. Learn. Res. 24 (2023)
Lan V. Truong
Fundamental limits and algorithms for sparse linear regression with sublinear sparsity. J. Mach. Learn. Res. 24 (2023)
Haixu Ma, Donglin Zeng, Yufeng Liu
Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments. J. Mach. Learn. Res. 24 (2023)
Simon Bartels, Wouter Boomsma, Jes Frellsen, Damien Garreau
Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition. J. Mach. Learn. Res. 24 (2023)
Tucker McElroy, Anindya Roy, Gaurab Hore
FLIP: A Utility Preserving Privacy Mechanism for Time Series. J. Mach. Learn. Res. 24 (2023)