题目：Testing Equivalence of Clustering

主讲人：宾夕法尼亚大学 马宗明副教授

主持人：西南财经大学统计学院 常晋源教授

时间：2020年5月29日（星期五）10:00-11:20

直播平台及会议ID：腾讯会议，715 897 972

报告摘要：

We test whether two datasets share a common clustering structure. As a leading example, we focus on comparing clustering structures in two independent random samples from two mixtures of multivariate Gaussian distributions. Mean parameters of these Gaussian distributions are treated as potentially unknown nuisance parameters and are allowed to differ. Assuming knowledge of mean parameters, we first determine the phase diagram of the testing problem over the entire range of signal-to-noise ratios by providing both lower bounds and tests that achieve them. When nuisance parameters are unknown, we propose tests that achieve the detection boundary adaptively as long as ambient dimensions of the datasets grow at a sub-linear rate with the sample size. The talk is based on a joint work with Chao Gao.

主讲人简介：

Zongming Ma is an Associate Professor of Statistics at the Wharton School of the University of Pennsylvania. His research interest includes network data analysis, high dimensional statistics and nonparametric statistics. He is the recipient of a Sloan Fellowship and an NSF CAREER Award.