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

• Resource-Efficient Neural Networks for Embedded Systems

  Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek, Holger Fröning, Franz Pernkopf, Zoubin Ghahramani (50):1−51, 2024 PDF BibTeX

• Optimal First-Order Algorithms as a Function of Inequalities

  Chanwoo Park, Ernest K. Ryu (51):1−66, 2024 codePDF BibTeX

• Axiomatic effect propagation in structural causal models

  Raghav Singal, George Michailidis (52):1−71, 2024 PDF BibTeX

• Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks

  Dong-Young Lim, Sotirios Sabanis (53):1−52, 2024 PDF BibTeX

• Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization

  Daniel LeJeune, Jiayu Liu, Reinhard Heckel (54):1−37, 2024 codePDF BibTeX

• Revisiting RIP Guarantees for Sketching Operators on Mixture Models

  Ayoub Belhadji, Rémi Gribonval (55):1−68, 2024 PDF BibTeX

• A projected semismooth Newton method for a class of nonconvex composite programs with strong prox-regularity

  Jiang Hu, Kangkang Deng, Jiayuan Wu, Quanzheng Li (56):1−32, 2024 PDF BibTeX

• Data Thinning for Convolution-Closed Distributions

  Anna Neufeld, Ameer Dharamshi, Lucy L. Gao, Daniela Witten (57):1−35, 2024 codePDF BibTeX

• Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification

  Natalie S. Frank, Jonathan Niles-Weed (58):1−41, 2024 PDF BibTeX

• Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics

  Noga Mudrik, Yenho Chen, Eva Yezerets, Christopher J. Rozell, Adam S. Charles (59):1−44, 2024 codePDF BibTeX

• Causal-learn: Causal Discovery in Python

  Yujia Zheng, Biwei Huang, Wei Chen, Joseph Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang (60):1−8, 2024 codePDF BibTeX

• Scaling the Convex Barrier with Sparse Dual Algorithms

  Alessandro De Palma, Harkirat Singh Behl, Rudy Bunel, Philip H.S. Torr, M. Pawan Kumar (61):1−51, 2024 codePDF BibTeX

• Low-rank Variational Bayes correction to the Laplace method

  Janet van Niekerk, Haavard Rue (62):1−25, 2024 codePDF BibTeX

• An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates

  Jessie Finocchiaro, Rafael M. Frongillo, Bo Waggoner (63):1−60, 2024 PDF BibTeX

• Mathematical Framework for Online Social Media Auditing

  Wasim Huleihel, Yehonathan Refael (64):1−40, 2024 PDF BibTeX

• Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions

  Stanislas Ducotterd, Alexis Goujon, Pakshal Bohra, Dimitris Perdios, Sebastian Neumayer, Michael Unser (65):1−30, 2024 codePDF BibTeX

• On Unbiased Estimation for Partially Observed Diffusions

  Jeremy Heng, Jeremie Houssineau, Ajay Jasra (66):1−66, 2024 codePDF BibTeX

• Off-Policy Action Anticipation in Multi-Agent Reinforcement Learning

  Ariyan Bighashdel, Daan de Geus, Pavol Jancura, Gijs Dubbelman (67):1−31, 2024 codePDF BibTeX

• Learnability of Linear Port-Hamiltonian Systems

  Juan-Pablo Ortega, Daiying Yin (68):1−56, 2024 codePDF BibTeX

• Tangential Wasserstein Projections

  Florian Gunsilius, Meng Hsuan Hsieh, Myung Jin Lee (69):1−41, 2024 codePDF BibTeX

• Scaling Instruction-Finetuned Language Models

  Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei (70):1−53, 2024 PDF BibTeX

• Policy Gradient Methods in the Presence of Symmetries and State Abstractions

  Prakash Panangaden, Sahand Rezaei-Shoshtari, Rosie Zhao, David Meger, Doina Precup (71):1−57, 2024 codePDF BibTeX

• Pareto Smoothed Importance Sampling

  Aki Vehtari, Daniel Simpson, Andrew Gelman, Yuling Yao, Jonah Gabry (72):1−58, 2024 codePDF BibTeX

• Data Summarization via Bilevel Optimization

  Zalán Borsos, Mojmír Mutný, Marco Tagliasacchi, Andreas Krause (73):1−53, 2024 PDF BibTeX

• Differentially private methods for managing model uncertainty in linear regression

  Víctor Peña, Andrés F. Barrientos (74):1−44, 2024 PDF BibTeX

• Towards Explainable Evaluation Metrics for Machine Translation

  Christoph Leiter, Piyawat Lertvittayakumjorn, Marina Fomicheva, Wei Zhao, Yang Gao, Steffen Eger (75):1−49, 2024 PDF BibTeX

• Distributed Estimation on Semi-Supervised Generalized Linear Model

  Jiyuan Tu, Weidong Liu, Xiaojun Mao (76):1−41, 2024 PDF BibTeX

• Unlabeled Principal Component Analysis and Matrix Completion

  Yunzhen Yao, Liangzu Peng, Manolis C. Tsakiris (77):1−38, 2024 codePDF BibTeX

• Functional Directed Acyclic Graphs

  Kuang-Yao Lee, Lexin Li, Bing Li (78):1−48, 2024 PDF BibTeX

• Choosing the Number of Topics in LDA Models – A Monte Carlo Comparison of Selection Criteria

  Victor Bystrov, Viktoriia Naboka-Krell, Anna Staszewska-Bystrova, Peter Winker (79):1−30, 2024 codePDF BibTeX

• ptwt - The PyTorch Wavelet Toolbox

  Moritz Wolter, Felix Blanke, Jochen Garcke, Charles Tapley Hoyt (80):1−7, 2024 codePDF BibTeX

• Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions

  Maksim Velikanov, Dmitry Yarotsky (81):1−78, 2024 PDF BibTeX

• On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains

  Yicheng Li, Zixiong Yu, Guhan Chen, Qian Lin (82):1−47, 2024 PDF BibTeX

• Win: Weight-Decay-Integrated Nesterov Acceleration for Faster Network Training

  Pan Zhou, Xingyu Xie, Zhouchen Lin, Kim-Chuan Toh, Shuicheng Yan (83):1−74, 2024 codePDF BibTeX

• On the Learnability of Out-of-distribution Detection

  Zhen Fang, Yixuan Li, Feng Liu, Bo Han, Jie Lu (84):1−83, 2024 PDF BibTeX

• Learning Non-Gaussian Graphical Models via Hessian Scores and Triangular Transport

  Ricardo Baptista, Youssef Marzouk, Rebecca Morrison, Olivier Zahm (85):1−46, 2024 codePDF BibTeX

• A Semi-parametric Estimation of Personalized Dose-response Function Using Instrumental Variables

  Wei Luo, Yeying Zhu, Xuekui Zhang, Lin Lin (86):1−38, 2024 PDF BibTeX

• Spatial meshing for general Bayesian multivariate models

  Michele Peruzzi, David B. Dunson (87):1−49, 2024 codePDF BibTeX

• Nonparametric Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks

  Guohao Shen, Yuling Jiao, Yuanyuan Lin, Joel L. Horowitz, Jian Huang (88):1−75, 2024 PDF BibTeX

• Minimax Rates for High-Dimensional Random Tessellation Forests

  Eliza O'Reilly, Ngoc Mai Tran (89):1−32, 2024 PDF BibTeX

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

  Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy (90):1−49, 2024 PDF BibTeX

• The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective

  Chi-Heng Lin, Chiraag Kaushik, Eva L. Dyer, Vidya Muthukumar (91):1−85, 2024 codePDF BibTeX

• Exploration of the Search Space of Gaussian Graphical Models for Paired Data

  Alberto Roverato, Dung Ngoc Nguyen (92):1−41, 2024 PDF BibTeX

• Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces

  Rui Wang, Yuesheng Xu, Mingsong Yan (93):1−45, 2024 PDF BibTeX

• Overparametrized Multi-layer Neural Networks: Uniform Concentration of Neural Tangent Kernel and Convergence of Stochastic Gradient Descent

  Jiaming Xu, Hanjing Zhu (94):1−83, 2024 PDF BibTeX

• A General Framework for the Analysis of Kernel-based Tests

  Tamara Fernández, Nicolás Rivera (95):1−40, 2024 PDF BibTeX

• MAP- and MLE-Based Teaching

  Hans Ulrich Simon, Jan Arne Telle (96):1−34, 2024 PDF BibTeX

• Scaling Speech Technology to 1,000+ Languages

  Vineel Pratap, Andros Tjandra, Bowen Shi, Paden Tomasello, Arun Babu, Sayani Kundu, Ali Elkahky, Zhaoheng Ni, Apoorv Vyas, Maryam Fazel-Zarandi, Alexei Baevski, Yossi Adi, Xiaohui Zhang, Wei-Ning Hsu, Alexis Conneau, Michael Auli (97):1−52, 2024 codePDF BibTeX

• Adaptivity and Non-stationarity: Problem-dependent Dynamic Regret for Online Convex Optimization

  Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou (98):1−52, 2024 PDF BibTeX

• Semi-supervised Inference for Block-wise Missing Data without Imputation

  Shanshan Song, Yuanyuan Lin, Yong Zhou (99):1−36, 2024 PDF BibTeX

• Materials Discovery using Max K-Armed Bandit

  Nobuaki Kikkawa, Hiroshi Ohno (100):1−40, 2024 PDF BibTeX

• AMLB: an AutoML Benchmark

  Pieter Gijsbers, Marcos L. P. Bueno, Stefan Coors, Erin LeDell, Sébastien Poirier, Janek Thomas, Bernd Bischl, Joaquin Vanschoren (101):1−65, 2024 codePDF BibTeX

• Nonparametric Regression for 3D Point Cloud Learning

  Xinyi Li, Shan Yu, Yueying Wang, Guannan Wang, Li Wang, Ming-Jun Lai (102):1−56, 2024 codePDF BibTeX

• Information Processing Equalities and the Information–Risk Bridge

  Robert C. Williamson, Zac Cranko (103):1−53, 2024 PDF BibTeX

• Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data

  Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini (104):1−47, 2024 PDF BibTeX

• Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need?

  Roel Bouman, Zaharah Bukhsh, Tom Heskes (105):1−34, 2024 codePDF BibTeX

• PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design

  Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick (106):1−26, 2024 codePDF BibTeX

• Random Forest Weighted Local Fréchet Regression with Random Objects

  Rui Qiu, Zhou Yu, Ruoqing Zhu (107):1−69, 2024 codePDF BibTeX

• QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration

  Felix Chalumeau, Bryan Lim, Raphaël Boige, Maxime Allard, Luca Grillotti, Manon Flageat, Valentin Macé, Guillaume Richard, Arthur Flajolet, Thomas Pierrot, Antoine Cully (108):1−16, 2024 codePDF BibTeX

• Neural Hilbert Ladders: Multi-Layer Neural Networks in Function Space

  Zhengdao Chen (109):1−65, 2024 PDF BibTeX

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

  Borja Rodríguez-Gálvez, Ragnar Thobaben, Mikael Skoglund (110):1−43, 2024 PDF BibTeX