JMLR 2026

137 papers

Hierarchical Causal Models

Eli N. Weinstein, David M. Blei

Optimizing Attention with Mirror Descent: Generalized Max-Margin Token Selection

Addison Kristanto Julistiono, Davoud Ataee Tarzanagh, Navid Azizan

Adaptive Forward Stepwise: A Method for High Sparsity Regression

Ivy Zhang, Robert Tibshirani

Optimization and Generalization of Gradient Descent for Shallow ReLU Networks with Minimal Width

Yunwen Lei, Puyu Wang, Yiming Ying, Ding-Xuan Zhou

Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection

Steven Adams, Andrea Patane, Morteza Lahijanian, Luca Laurenti

CHANI: Correlation-based Hawkes Aggregation of Neurons with bio-Inspiration

Sophie Jaffard, Samuel Vaiter, Patricia Reynaud-Bouret

Persistence Diagrams Estimation of Multivariate Piecewise Hölder-continuous Signals

Hugo Henneuse

Exploring Novel Uncertainty Quantification through Forward Intensity Function Modeling

Yudong Wang, Zhi-Sheng Ye, Cheng Yong Tang

Generative Bayesian Inference with GANs

Yuexi Wang, Veronika Ročková

Communication-efficient Distributed Statistical Inference for Massive Data with Heterogeneous Auxiliary Information

Miaomiao Yu, Zhongfeng Jiang, Jiaxuan Li, Yong Zhou

Zijian Guo, Wei Yuan, Cunhui Zhang

Refined Risk Bounds for Unbounded Losses via Transductive Priors

Jian Qian, Alexander Rakhlin, Nikita Zhivotovskiy

A Common Interface for Automatic Differentiation

Guillaume Dalle, Adrian Hill

LazyDINO: Fast, Scalable, and Efficiently Amortized Bayesian Inversion via Structure-Exploiting and Surrogate-Driven Measure Transport

Lianghao Cao, Joshua Chen, Michael Brennan, Thomas O'Leary-Roseberry, Youssef Marzouk

The Distribution of Ridgeless Least Squares Interpolators

Qiyang Han, Xiaocong Xu

Nonparametric Estimation of a Factorizable Density using Diffusion Models

Hyeok Kyu Kwon, Dongha Kim, Ilsang Ohn, Minwoo Chae

Learning Bayesian Network Classifiers to Minimize Class Variable Parameters

Shouta Sugahara, Koya Kato, James Cussens, Maomi Ueno

Simulation-based Calibration of Uncertainty Intervals under Approximate Bayesian Estimation

Terrance D. Savitsky, Julie Gershunskaya

An Anytime Algorithm for Good Arm Identification

Marc Jourdan, Andrée Delahaye-Duriez, Clémence Réda

Extrapolated Markov Chain Oversampling Method for Imbalanced Text Classification

Aleksi Avela, Pauliina Ilmonen

Neural Network Parameter-optimization of Gaussian Pre-marginalized Directed Acyclic Graphs

Mehrzad Saremi

Flexible Functional Treatment Effect Estimation

Jiayi Wang, Raymond K. W. Wong, Xiaoke Zhang, Kwun Chuen Gary Chan

Error Analysis for Deep ReLU Feedforward Density-Ratio Estimation with Bregman Divergence

Siming Zheng, Guohao Shen, Yuanyuan Lin, Jian Huang

A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design

Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan

UQLM: A Python Package for Uncertainty Quantification in Large Language Models

Dylan Bouchard, Mohit Singh Chauhan, David Skarbrevik, Ho-Kyeong Ra, Viren Bajaj

Nonlinear function-on-function regression by RKHS

Peijun Sang, Bing Li

Nonlocal Techniques for the Analysis of Deep ReLU Neural Network Approximations

Cornelia Schneider, Mario Ullrich, Jan Vybíral

A Data-Augmented Contrastive Learning Approach to Nonparametric Density Estimation

Chenghao Li, Yuanyuan Lin

Guaranteed Nonconvex Low-Rank Tensor Estimation via Scaled Gradient Descent

Tong Wu

skwdro: a library for Wasserstein distributionally robust machine learning

Vincent Florian, Waïss Azizian, Franck Iutzeler, Jérôme Malick

Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation

Bohan Wu, David M. Blei

Stochastic Gradient Methods: Bias, Stability and Generalization

Shuang Zeng, Yunwen Lei

Classification Under Local Differential Privacy with Model Reversal and Model Averaging

Caihong Qin, Yang Bai

Identifying Weight-Variant Latent Causal Models

Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang

Efficient frequent directions algorithms for approximate decomposition of matrices and higher-order tensors

Maolin Che, Yimin Wei, Hong Yan

Online Detection of Changes in Moment--Based Projections: When to Retrain Deep Learners or Update Portfolios?

Ansgar Steland

The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks

Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs