Wenxin Zhou


Department of Mathematical Sciences
University of California, San Diego
9500 Gilman Dr.
La Jolla, CA 92093

Phone: 858-534-2640
E-mail: wez243@ucsd.edu
Office: AP&M 6131




I am an Associate Professor in the Department of Mathematical Sciences at the University of California, San Diego [Google Scholar & CV].

My recent research interests center around the development and analysis of statistical methods (estimation and inference) and optimization tools for structured high-dimensional data problems, including sparse regression, low-rank, and nonparametric models. The main focus is to develop robust and quantile-based methods in settings where the error distribution is heavy-tailed and/or heteroscedastic. I also work on developing and analyzing methods (from a statistical perspective) with nontraditional data types, such as distributed data, streaming/online data, multi-source data, and data subject to privacy concerns.



Complete Publications (arXiv)

Selected Publications

Communication-constrained distributed quantile regression with optimal statistical guarantees
with Kean Ming Tan and Heather Battey
Journal of Machine Learning Research, to appear, 2022+
[preprint]

Scalable estimation and inference for censored quantile regression process
with Xuming He, Xiaoou Pan and Kean Ming Tan
The Annals of Statistics, to appear, 2022+
[preprint] [supplement] [R code]

Smoothed quantile regression with large-scale inference
with Xuming He, Xiaoou Pan and Kean Ming Tan
Journal of Econometrics, to appear, 2022+
[DOI] [R package] [Python code] [slides]

High-dimensional quantile regression: convolution smoothing and concave regularization
with Kean Ming Tan and Lan Wang
Journal of the Royal Statistical Society: Series B, 84(1): 205-233,2022
[DOI] [supplement] [R package] [Python code]

Multiplier bootstrap for quantile regression: Non-asymptotic theory under random design
with Xiaoou Pan
Information and Inference: A Journal of the IMA, 10, 813-861, 2021
[DOI] [R code]

A new principle for tuning-free Huber regression
with Lili Wang, Chao Zheng and Wen Zhou
Statistica Sinica, 31, 2153-2177, 2021
[DOI] [supplement] [R package]

Iteratively reweighted l1-penalized robust regression
with Xiaoou Pan and Qiang Sun
Electronic Journal of Statistics, 15, 3287-3348, 2021
[DOI] [R package] [Python code]

Robust inference via multiplier bootstrap
with Xi Chen
The Annals of Statistics, 48, 1665-1691, 2020
[DOI] [supplement] [Matlab code]

Adaptive Huber regression
with Qiang Sun and Jianqing Fan
Journal of the American Statistical Association, 115, 254-265, 2020
[DOI] [arXiv] [R package] [slides]

FarmTest: Factor-adjusted robust multiple testing with approximate false discovery control
with Jianqing Fan, Yuan Ke and Qiang Sun
Journal of the American Statistical Association, 114, 1880-1893, 2019
[DOI] [R package]

User-friendly covariance estimation for heavy-tailed distributions
with Yuan Ke, Stanislav Minsker, Zhao Ren and Qiang Sun
Statistical Science, 34, 454-471, 2019
[DOI]

A new perspective on robust M-estimation: Finite sample theory and applications to dependence-adjusted multiple testing
with Koushiki Bose, Jianqing Fan and Han Liu
The Annals of Statistics, 46, 1904-1931, 2018
[DOI] [arXiv]

Are discoveries spurious? Distributions of maximum spurious correlations and their applications
with Jianqing Fan and Qi-Man Shao
The Annals of Statistics, 46, 989-1017, 2018
[DOI] [arXiv] [slides]

Max-norm optimization for robust matrix recovery
with Ethan X. Fang, Han Liu and Kim-Chuan Toh
Mathematical Programming, Series B, 167, 5-35, 2018
[DOI] [arXiv]

Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity
with Jinyuan Chang, Chao Zheng and Wen Zhou
Biometrics, 73, 1300-1310, 2017
[DOI] [arXiv] [slides]

Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering
with Jinyuan Chang, Wen Zhou and Lan Wang
Biometrics, 73, 31-41, 2017
[DOI] [arXiv]

Guarding against spurious discoveries in high dimensions
with Jianqing Fan
Journal of Machine Learning Research, 17(203), 1-34, 2016
[DOI] [arXiv] [slides]

Nonparametric covariate-adjusted regression
with Aurore Delaigle and Peter Hall
The Annals of Statistics, 44, 2190-2220, 2016
[DOI]

Cramér-type moderate deviations for Studentized two-sample U-statistics with applications
with Jinyuan Chang and Qi-Man Shao
The Annals of Statistics, 44, 1931-1956, 2016
[DOI] [slides]

Matrix completion via max-norm constrained optimization
with Tony T. Cai
Electronic Journal of Statistics, 10, 1493-1525, 2016
[DOI]

Cramér type moderate deviation theorems for self-normalized processes
with Qi-Man Shao
Bernoulli, 22, 2029-2079, 2016
[DOI]

Nonparametric and parametric estimators of prevalence from group testing data with aggregated covariates
with Aurore Delaigle
Journal of the American Statistical Association, 110, 1785-1796, 2015
[DOI]

Necessary and sufficient conditions for the asymptotic distributions of coherence of ultra-high dimensional random matrices
with Qi-Man Shao
The Annals of Probability, 42, 623-648, 2014
[DOI] [arXiv] [slides]

A max-norm constrained minimization approach to 1-bit matrix completion
with Tony T. Cai
Journal of Machine Learning Research, 14, 3619-3647, 2013
[DOI]

Review Articles

Principal component analysis for big data
with Jianqing Fan, Qiang Sun and Ziwei Zhu
Wiley StatsRef: Statistics Reference Online, 2018
[DOI] [pdf]

Self-normalization: Taming a wild population in a heavy-tailed world
with Qi-Man Shao
Applied Mathematics-A Journal of Chinese Universities, 32, 253-269, 2017
[DOI]

Editorial Service

2022-Present: Associate Editor, Annals of Statistics
2022-Present: Associate Editor, Annals of Applied Probability
2022-Present: Associate Editor, JRSSB
2020-Present: Associate Editor, Statistics: A Jnl of Theor. & Appl. Stat

Bio

2021-Present: Associate Professor, Department of Mathematical Sciences, University of California, San Diego
2017-21: Assistant Professor, Department of Mathematics, University of California, San Diego
2015-17: Postdoctoral Research Associate, Department of Operations Research and Financial Engineering, Princeton University
2013-15: Research Fellow, School of Mathematics and Statistics, University of Melbourne