Nonparametric estimation in high-dimensional settings addresses the challenge of inferring complex structures from data without prespecifying a fixed parametric form. As the number of variables grows, ...

High-dimensional model selection in multivariate statistics addresses the challenge of choosing an appropriate statistical model when both the number of variables and the sample size can grow large ...

This book offers a comprehensive framework for mastering the complexities of learning high-dimensional sparse graphical models through the use of conditional independence tests. These tests are ...

Yihong Wu, whose work lies at the intersection of high-dimensional statistics, information theory, and computer science, was recently appointed the James A. Attwood Professor of Statistics and Data ...