JMLR 2024

422 papers

An Algorithm with Optimal Dimension-Dependence for Zero-Order Nonsmooth Nonconvex Stochastic Optimization

Guy Kornowski, Ohad Shamir

Linear Distance Metric Learning with Noisy Labels

Meysam Alishahi, Anna Little, Jeff M. Phillips

OpenBox: A Python Toolkit for Generalized Black-box Optimization

Huaijun Jiang, Yu Shen, Yang Li, Beicheng Xu, Sixian Du

Generative Adversarial Ranking Nets

Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao

Predictive Inference with Weak Supervision

Maxime Cauchois, Suyash Gupta, Alnur Ali, John C. Duchi

Functions with average smoothness: structure, algorithms, and learning

Yair Ashlagi, Lee-Ad Gottlieb, Aryeh Kontorovich

Differentially Private Data Release for Mixed-type Data via Latent Factor Models

Yanqing Zhang, Qi Xu, Niansheng Tang, Annie Qu

The Non-Overlapping Statistical Approximation to Overlapping Group Lasso

Mingyu Qi, Tianxi Li

Faster Rates of Differentially Private Stochastic Convex Optimization

Jinyan Su, Lijie Hu, Di Wang

Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization

O. Deniz Akyildiz, Sotirios Sabanis

Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits

Junpei Komiyama, Edouard Fouché, Junya Honda

Stable Implementation of Probabilistic ODE Solvers

Nicholas Krämer, Philipp Hennig

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

Borja Rodríguez-Gálvez, Ragnar Thobaben, Mikael Skoglund

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

Zhengdao Chen

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

Felix Chalumeau, Bryan Lim, Raphael Boige, Maxime Allard, Luca Grillotti

Random Forest Weighted Local Fréchet Regression with Random Objects

Rui Qiu, Zhou Yu, Ruoqing Zhu

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

Alexandre Duval, victor schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García

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

Roel Bouman, Zaharah Bukhsh, Tom Heskes

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

Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini

Information Processing Equalities and the Information–Risk Bridge

Robert C. Williamson, Zac Cranko

Nonparametric Regression for 3D Point Cloud Learning

Xinyi Li, Shan Yu, Yueying Wang, Guannan Wang, Li Wang

AMLB: an AutoML Benchmark

Pieter Gijsbers, Marcos L. P. Bueno, Stefan Coors, Erin LeDell, Sébastien Poirier

Materials Discovery using Max K-Armed Bandit

Nobuaki Kikkawa, Hiroshi Ohno

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

Shanshan Song, Yuanyuan Lin, Yong Zhou

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

Peng Zhao, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou

Scaling Speech Technology to 1,000+ Languages

Vineel Pratap, Andros Tjandra, Bowen Shi, Paden Tomasello, Arun Babu

MAP- and MLE-Based Teaching

Hans Ulrich Simon, Jan Arne Telle

A General Framework for the Analysis of Kernel-based Tests

Tamara Fernandez, Nicolas Rivera

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

Jiaming Xu, Hanjing Zhu

Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces

Rui Wang, Yuesheng Xu, Mingsong Yan

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

Alberto Roverato, Dung Ngoc Nguyen

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

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

Joshua Cutler, Mateo Diaz, Dmitriy Drusvyatskiy

Minimax Rates for High-Dimensional Random Tessellation Forests

Eliza O'Reilly, Ngoc Mai Tran

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

Guohao Shen, Yuling Jiao, Yuanyuan Lin, Joel L. Horowitz, Jian Huang

Spatial meshing for general Bayesian multivariate models

Michele Peruzzi, David B. Dunson

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

Wei Luo, Yeying Zhu, Xuekui Zhang, Lin Lin

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

Ricardo Baptista, Rebecca Morrison, Olivier Zahm, Youssef Marzouk

On the Learnability of Out-of-distribution Detection

Zhen Fang, Yixuan Li, Feng Liu, Bo Han, Jie Lu

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

Pan Zhou, Xingyu Xie, Zhouchen Lin, Kim-Chuan Toh, Shuicheng Yan

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

Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions

Maksim Velikanov, Dmitry Yarotsky

ptwt - The PyTorch Wavelet Toolbox

Moritz Wolter, Felix Blanke, Jochen Garcke, Charles Tapley Hoyt

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

Functional Directed Acyclic Graphs

Kuang-Yao Lee, Lexin Li, Bing Li

Unlabeled Principal Component Analysis and Matrix Completion

Yunzhen Yao, Liangzu Peng, Manolis C. Tsakiris

Distributed Estimation on Semi-Supervised Generalized Linear Model

Jiyuan Tu, Weidong Liu, Xiaojun Mao

Towards Explainable Evaluation Metrics for Machine Translation

Christoph Leiter, Piyawat Lertvittayakumjorn, Marina Fomicheva, Wei Zhao, Yang Gao

Differentially private methods for managing model uncertainty in linear regression

Víctor Peña, Andrés F. Barrientos

Data Summarization via Bilevel Optimization

Zalán Borsos, Mojmir Mutny, Marco Tagliasacchi, Andreas Krause

Pareto Smoothed Importance Sampling

Aki Vehtari, Daniel Simpson, Andrew Gelman, Yuling Yao, Jonah Gabry

Policy Gradient Methods in the Presence of Symmetries and State Abstractions

Prakash Panangaden, Sahand Rezaei-Shoshtari, Rosie Zhao, David Meger, Doina Precup

Scaling Instruction-Finetuned Language Models

Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay

Tangential Wasserstein Projections

Florian Gunsilius, Meng Hsuan Hsieh, Myung Jin Lee

Learnability of Linear Port-Hamiltonian Systems

Juan-Pablo Ortega, Daiying Yin

Off-Policy Action Anticipation in Multi-Agent Reinforcement Learning

Ariyan Bighashdel, Daan de Geus, Pavol Jancura, Gijs Dubbelman

On Unbiased Estimation for Partially Observed Diffusions

Jeremy Heng, Jeremie Houssineau, Ajay Jasra

Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions

Stanislas Ducotterd, Alexis Goujon, Pakshal Bohra, Dimitris Perdios, Sebastian Neumayer

Mathematical Framework for Online Social Media Auditing

Wasim Huleihel, Yehonathan Refael

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

Jessie Finocchiaro, Rafael M. Frongillo, Bo Waggoner

Low-rank Variational Bayes correction to the Laplace method

Janet van Niekerk, Haavard Rue

Scaling the Convex Barrier with Sparse Dual Algorithms

Alessandro De Palma, Harkirat Singh Behl, Rudy Bunel, Philip H.S. Torr, M. Pawan Kumar

Causal-learn: Causal Discovery in Python

Yujia Zheng, Biwei Huang, Wei Chen, Joseph Ramsey, Mingming Gong

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

Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification

Natalie S. Frank, Jonathan Niles-Weed

Data Thinning for Convolution-Closed Distributions

Anna Neufeld, Ameer Dharamshi, Lucy L. Gao, Daniela Witten

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

Jiang Hu, Kangkang Deng, Jiayuan Wu, Quanzheng Li

Revisiting RIP Guarantees for Sketching Operators on Mixture Models

Ayoub Belhadji, Remi Gribonval

Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization

Daniel LeJeune, Jiayu Liu, Reinhard Heckel

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

Dong-Young Lim, Sotirios Sabanis

Axiomatic effect propagation in structural causal models

Raghav Singal, George Michailidis

Optimal First-Order Algorithms as a Function of Inequalities

Chanwoo Park, Ernest K. Ryu

Resource-Efficient Neural Networks for Embedded Systems

Wolfgang Roth, Günther Schindler, Bernhard Klein, Robert Peharz, Sebastian Tschiatschek

Trained Transformers Learn Linear Models In-Context

Ruiqi Zhang, Spencer Frei, Peter L. Bartlett

Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees

Nachuan Xiao, Xiaoyin Hu, Xin Liu, Kim-Chuan Toh

Efficient Modality Selection in Multimodal Learning

Yifei He, Runxiang Cheng, Gargi Balasubramaniam, Yao-Hung Hubert Tsai, Han Zhao

A Multilabel Classification Framework for Approximate Nearest Neighbor Search

Ville Hyvönen, Elias Jääsaari, Teemu Roos

Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization

Lorenzo Pacchiardi, Rilwan A. Adewoyin, Peter Dueben, Ritabrata Dutta

Multiple Descent in the Multiple Random Feature Model

Xuran Meng, Jianfeng Yao, Yuan Cao

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

Ye He, Tyler Farghly, Krishnakumar Balasubramanian, Murat A. Erdogdu

Invariant and Equivariant Reynolds Networks

Akiyoshi Sannai, Makoto Kawano, Wataru Kumagai

Personalized PCA: Decoupling Shared and Unique Features

Naichen Shi, Raed AL Kontar

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

George H. Chen

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

Convergence for nonconvex ADMM, with applications to CT imaging

Rina Foygel Barber, Emil Y. Sidky

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

T. Tony Cai, Hongji Wei

Sparse NMF with Archetypal Regularization: Computational and Robustness Properties

Kayhan Behdin, Rahul Mazumder

Deep Network Approximation: Beyond ReLU to Diverse Activation Functions

Shijun Zhang, Jianfeng Lu, Hongkai Zhao

Effect-Invariant Mechanisms for Policy Generalization

Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan Murphy, Jonas Peters

Pygmtools: A Python Graph Matching Toolkit

Runzhong Wang, Ziao Guo, Wenzheng Pan, Jiale Ma, Yikai Zhang

Heterogeneous-Agent Reinforcement Learning

Yifan Zhong, Jakub Grudzien Kuba, Xidong Feng, Siyi Hu, Jiaming Ji

Sample-efficient Adversarial Imitation Learning

Dahuin Jung, HyunGyu Lee, Sungroh Yoon

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

Benjamin Gess, Sebastian Kassing, Vitalii Konarovskyi

Rates of convergence for density estimation with generative adversarial networks

Nikita Puchkin, Sergey Samsonov, Denis Belomestny, Eric Moulines, Alexey Naumov

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

Mathis Chagneux, Elisabeth Gassiat, Pierre Gloaguen, Sylvain Le Corff

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

Stephan Wojtowytsch

Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees

Alexander Terenin, David R. Burt, Artem Artemev, Seth Flaxman, Mark van der Wilk

On Tail Decay Rate Estimation of Loss Function Distributions

Etrit Haxholli, Marco Lorenzi

Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces

Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao

Post-Regularization Confidence Bands for Ordinary Differential Equations

Xiaowu Dai, Lexin Li