Wenxin Zhou

24 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0002-2761-485X

University of Illinois at Chicago

Publications

• Deep Neural Expected Shortfall Regression with Tail-Robustness — Journal of Machine Learning Research 2026 (name-matched, not ORCID-linked)
• Estimation and Inference for Nonparametric Expected Shortfall Regression over RKHS — Journal of the American Statistical Association 2025
• Online Quantile Regression — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Private Optimal Inventory Policy Learning for Feature-Based Newsvendor with Unknown Demand — Management Science 2025
• High-Dimensional Expected Shortfall Regression — Journal of the American Statistical Association 2025
• On Inference for the Support Vector Machine — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Linear Hypothesis Testing in High-Dimensional Expected Shortfall Regression with Heavy-Tailed Errors — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• How do noise tails impact on deep ReLU networks? — The Annals of Statistics 2024
• Robust estimation and inference for expected shortfall regression with many regressors — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2023
• Scalable estimation and inference for censored quantile regression process — The Annals of Statistics 2022
• Communication-Constrained Distributed Quantile Regression with Optimal Statistical Guarantees — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
• High-dimensional quantile regression: Convolution smoothing and concave regularization — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2022
• Robust inference via multiplier bootstrap — The Annals of Statistics 2020
• Adaptive Huber Regression — Journal of the American Statistical Association 2020
• FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control — Journal of the American Statistical Association 2019
• Are discoveries spurious? Distributions of maximum spurious correlations and their applications — The Annals of Statistics 2018
• A new perspective on robust $M$-estimation: Finite sample theory and applications to dependence-adjusted multiple testing — The Annals of Statistics 2018
• Guarding against Spurious Discoveries in High Dimensions — Journal of Machine Learning Research 2016 (name-matched, not ORCID-linked)
• Cramér-type moderate deviations for Studentized two-sample $U$-statistics with applications — The Annals of Statistics 2016
• Nonparametric covariate-adjusted regression — The Annals of Statistics 2016
• Nonparametric and Parametric Estimators of Prevalence From Group Testing Data With Aggregated Covariates — Journal of the American Statistical Association 2015
• A Max-Norm Constrained Minimization Approach to 1-Bit Matrix Completion — Journal of Machine Learning Research 2013 (name-matched, not ORCID-linked)
• Feature-Rich, Data-Private: A Sparse Learning Framework for the High-Dimensional Newsvendor — Operations Research
• Adapting to Noise Tails in Private Linear Regression — Journal of the American Statistical Association