JMLR Volume 25

• On Truthing Issues in Supervised Classification

  Jonathan K. Su (1):1−91, 2024 PDF BibTeX

• Lower Complexity Bounds of Finite-Sum Optimization Problems: The Results and Construction

  Yuze Han, Guangzeng Xie, Zhihua Zhang (2):1−86, 2024 PDF BibTeX

• Power of knockoff: The impact of ranking algorithm, augmented design, and symmetric statistic

  Zheng Tracy Ke, Jun S. Liu, Yucong Ma (3):1−67, 2024 PDF BibTeX

• Fast Policy Extragradient Methods for Competitive Games with Entropy Regularization

  Shicong Cen, Yuting Wei, Yuejie Chi (4):1−48, 2024 PDF BibTeX

• Seeded Graph Matching for the Correlated Gaussian Wigner Model via the Projected Power Method

  Ernesto Araya, Guillaume Braun, Hemant Tyagi (5):1−43, 2024 codePDF BibTeX

• Model-Free Representation Learning and Exploration in Low-Rank MDPs

  Aditya Modi, Jinglin Chen, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal (6):1−76, 2024 PDF BibTeX

• Decorrelated Variable Importance

  Isabella Verdinelli, Larry Wasserman (7):1−27, 2024 PDF BibTeX

• On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models

  Yangjing Zhang, Ying Cui, Bodhisattva Sen, Kim-Chuan Toh (8):1−46, 2024 codePDF BibTeX

• Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment

  Zixian Yang, Xin Liu, Lei Ying (9):1−55, 2024 PDF BibTeX

• Modeling Random Networks with Heterogeneous Reciprocity

  Daniel Cirkovic, Tiandong Wang (10):1−40, 2024 PDF BibTeX

• Estimating the Minimizer and the Minimum Value of a Regression Function under Passive Design

  Arya Akhavan, Davit Gogolashvili, Alexandre B. Tsybakov (11):1−37, 2024 PDF BibTeX

• Critically Assessing the State of the Art in Neural Network Verification

  Matthias König, Annelot W. Bosman, Holger H. Hoos, Jan N. van Rijn (12):1−53, 2024 PDF BibTeX

• A Comparison of Continuous-Time Approximations to Stochastic Gradient Descent

  Stefan Ankirchner, Stefan Perko (13):1−55, 2024 PDF BibTeX

• Improving physics-informed neural networks with meta-learned optimization

  Alex Bihlo (14):1−26, 2024 PDF BibTeX

• On the Effect of Initialization: The Scaling Path of 2-Layer Neural Networks

  Sebastian Neumayer, Lénaïc Chizat, Michael Unser (15):1−24, 2024 PDF BibTeX

• Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond

  Nathan Kallus, Xiaojie Mao, Masatoshi Uehara (16):1−59, 2024 codePDF BibTeX

• On Sufficient Graphical Models

  Bing Li, Kyongwon Kim (17):1−64, 2024 PDF BibTeX

• Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box

  Ryan Giordano, Martin Ingram, Tamara Broderick (18):1−39, 2024 codePDF BibTeX

• Nonparametric Inference under B-bits Quantization

  Kexuan Li, Ruiqi Liu, Ganggang Xu, Zuofeng Shang (19):1−68, 2024 PDF BibTeX

• Iterate Averaging in the Quest for Best Test Error

  Diego Granziol, Nicholas P. Baskerville, Xingchen Wan, Samuel Albanie, Stephen Roberts (20):1−55, 2024 codePDF BibTeX

• Pursuit of the Cluster Structure of Network Lasso: Recovery Condition and Non-convex Extension

  Shotaro Yagishita, Jun-ya Gotoh (21):1−42, 2024 PDF BibTeX

• On the Generalization of Stochastic Gradient Descent with Momentum

  Ali Ramezani-Kebrya, Kimon Antonakopoulos, Volkan Cevher, Ashish Khisti, Ben Liang (22):1−56, 2024 PDF BibTeX

• Post-Regularization Confidence Bands for Ordinary Differential Equations

  Xiaowu Dai, Lexin Li (23):1−51, 2024 PDF BibTeX

• Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces

  Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao (24):1−67, 2024 PDF BibTeX

• On Tail Decay Rate Estimation of Loss Function Distributions

  Etrit Haxholli, Marco Lorenzi (25):1−47, 2024 codePDF BibTeX

• Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees

  Alexander Terenin, David R. Burt, Artem Artemev, Seth Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge (26):1−36, 2024 codePDF BibTeX

• Optimal Bump Functions for Shallow ReLU networks: Weight Decay, Depth Separation, Curse of Dimensionality

  Stephan Wojtowytsch (27):1−49, 2024 PDF BibTeX

• Additive smoothing error in backward variational inference for general state-space models

  Mathis Chagneux, Elisabeth Gassiat, Pierre Gloaguen, Sylvain Le Corff (28):1−33, 2024 PDF BibTeX

• Rates of convergence for density estimation with generative adversarial networks

  Nikita Puchkin, Sergey Samsonov, Denis Belomestny, Eric Moulines, Alexey Naumov (29):1−47, 2024 PDF BibTeX

• Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic Gradient Descent

  Benjamin Gess, Sebastian Kassing, Vitalii Konarovskyi (30):1−27, 2024 PDF BibTeX

• Sample-efficient Adversarial Imitation Learning

  Dahuin Jung, Hyungyu Lee, Sungroh Yoon (31):1−32, 2024 PDF BibTeX

• Heterogeneous-Agent Reinforcement Learning

  Yifan Zhong, Jakub Grudzien Kuba, Xidong Feng, Siyi Hu, Jiaming Ji, Yaodong Yang (32):1−67, 2024 codePDF BibTeX

• Pygmtools: A Python Graph Matching Toolkit

  Runzhong Wang, Ziao Guo, Wenzheng Pan, Jiale Ma, Yikai Zhang, Nan Yang, Qi Liu, Longxuan Wei, Hanxue Zhang, Chang Liu, Zetian Jiang, Xiaokang Yang, Junchi Yan (33):1−7, 2024 codePDF BibTeX

• Effect-Invariant Mechanisms for Policy Generalization

  Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan Murphy, Jonas Peters (34):1−36, 2024 PDF BibTeX

• Deep Network Approximation: Beyond ReLU to Diverse Activation Functions

  Shijun Zhang, Jianfeng Lu, Hongkai Zhao (35):1−39, 2024 PDF BibTeX

• Sparse NMF with Archetypal Regularization: Computational and Robustness Properties

  Kayhan Behdin, Rahul Mazumder (36):1−62, 2024 codePDF BibTeX

• Distributed Gaussian Mean Estimation under Communication Constraints: Optimal Rates and Communication-Efficient Algorithms

  T. Tony Cai, Hongji Wei (37):1−63, 2024 PDF BibTeX

• Convergence for nonconvex ADMM, with applications to CT imaging

  Rina Foygel Barber, Emil Y. Sidky (38):1−46, 2024 codePDF BibTeX

• On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control

  Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang, Mengdi Wang, Alec Koppel (39):1−58, 2024 PDF BibTeX

• Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee

  George H. Chen (40):1−78, 2024 codePDF BibTeX

• Personalized PCA: Decoupling Shared and Unique Features

  Naichen Shi, Raed Al Kontar (41):1−82, 2024 codePDF BibTeX

• Invariant and Equivariant Reynolds Networks

  Akiyoshi Sannai, Makoto Kawano, Wataru Kumagai (42):1−36, 2024 codePDF BibTeX

• Mean-Square Analysis of Discretized Itô Diffusions for Heavy-tailed Sampling

  Ye He, Tyler Farghly, Krishnakumar Balasubramanian, Murat A. Erdogdu (43):1−44, 2024 PDF BibTeX

• Multiple Descent in the Multiple Random Feature Model

  Xuran Meng, Jianfeng Yao, Yuan Cao (44):1−49, 2024 PDF BibTeX

• Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization

  Lorenzo Pacchiardi, Rilwan A. Adewoyin, Peter Dueben, Ritabrata Dutta (45):1−64, 2024 codePDF BibTeX

• A Multilabel Classification Framework for Approximate Nearest Neighbor Search

  Ville Hyvönen, Elias Jääsaari, Teemu Roos (46):1−51, 2024 codePDF BibTeX

• Efficient Modality Selection in Multimodal Learning

  Yifei He, Runxiang Cheng, Gargi Balasubramaniam, Yao-Hung Hubert Tsai, Han Zhao (47):1−39, 2024 PDF BibTeX

• Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees

  Nachuan Xiao, Xiaoyin Hu, Xin Liu, Kim-Chuan Toh (48):1−53, 2024 PDF BibTeX

• Trained Transformers Learn Linear Models In-Context

  Ruiqi Zhang, Spencer Frei, Peter L. Bartlett (49):1−55, 2024 PDF BibTeX