Lingzhou Xue

Associate Professor of Statistics

Lingzhou Xue

Research Summary

High-dimensional statistics, statistical learning, optimization, econometrics, and statistical applications in biological science, environmental science, and social science.

Huck Affiliations

Links

Publication Tags

Covariance Matrix High Dimensional Testing Graphical Models Predictors Statistics Simulation Study Performance Data Analysis Gene Conditional Independence Sufficient Nonparametric Estimation Covariance Matrix Estimation Forecasting Discrete Data Factors Alternatives Time Series High Dimensional Data Methodology Regression Rate Of Convergence Additive Models Stiefel Manifold

Most Recent Publications

Wei Luo, Lingzhou Xue, Jiawei Yao, Xiufan Yu, 2022, Biometrika on p. 473-487

Kevin H. Lee, Qian Chen, Wayne Desarbo, Lingzhou Xue, 2022, Psychometrika on p. 83-106

Bingyuan Liu, Christopher Malon, Lingzhou Xue, Erik Kruus, 2022, Image and Vision Computing on p. 104469

Xiufan Yu, Danning Li, Lingzhou Xue, 2022, Journal of the American Statistical Association

Xiufan Yu, D Li, Lingzhou Xue, Runze Li, 2022, Journal of the American Statistical Association

Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold

Bokun Wang, Shiqian Ma, Lingzhou Xue, 2022, Journal of Machine Learning Research

Jun Tao, Bing Li, Lingzhou Xue, 2022, Journal of the American Statistical Association

Xiufan Yu, Jiawei Yao, Lingzhou Xue, 2022, Journal of Business and Economic Statistics on p. 342-354

Danning Li, A Srinivasan, Qian Chen, Lingzhou Xue, 2022, Journal of Business and Economic Statistics

Identification of microbial features in multivariate regression under false discovery rate control

Arun Srinivasan, Lingzhou Xue, Xiang Zhan, 2022, Computational Statistics and Data Analysis