报告题目 Title：Estimation and Inference in Multivariate Response Regression with Hidden Variables

报告人 Speaker：Yang Ning

报告人所在单位 Affiliation：Cornell University

时间 Time：2025-11-26 10:00

地点 Venue：Room 2201, Guanghua Eastern Main Tower, Fudan University (Handan Campus)

报告摘要 Abstract：In this talk, we consider multivariate regression with hidden variables, $Y = \Theta^TX + B^TZ  + E$, where $Y$ is a $m$-dimensional response vector, $X$ is a $p$-dimensional vector of observable features, $Z$ represents a $K$-dimensional vector of unobserved hidden variables, possibly correlated with $X$, and $E$ is an independent error. The number of hidden variables $K$ is unknown and both $m$ and $p$ are allowed (but not required) to grow with the sample size $n$. We address several fundamental challenges of this problem, (1) parameter identification, (2) estimation methods/non-asymptotic analysis, (3) asymptotic inference, and (4) generalizations to heteroscedastic errors and GLM. This talk is based on a sequence of works primarily with my students. Related papers include  https://arxiv.org/abs/2003.13844,  https://arxiv.org/pdf/2201.08003, https://arxiv.org/abs/2509.00196.

个人简介 Bio：Dr. Ning is an associate professor in the Department of Statistics and Data Science at Cornell University. He received his Ph.D in Biostatistics from the Johns Hopkins University and was a post-doc at Princeton University and University of Waterloo. His research interests focus on high-dimensional statistics, and statistical inference in machine learning problems.

海报Poster：Yang Ning 学术报告.jpg