DMS Statistics and Data Science Seminar

Speaker: Yaqing Chen (Rutgers University)

Title: Geometric Exploration of Random Objects Through Optimal Transport

Abstract: We propose new tools for the geometric exploration of data objects taking values in a general separable metric space. For a random object, we first introduce the concept of depth profiles. Specifically, the depth profile of a point in a metric space is the distribution of distances between the very point and the random object. Depth profiles can be harnessed to define transport ranks based on optimal transport, which capture the centrality and outlyingness of each element in the metric space with respect to the probability measure induced by the random object. We study the properties of transport ranks and show that they provide an effective device for detecting and visualizing patterns in samples of random objects. In particular, we establish the theoretical guarantees for the estimation of the depth profiles and the transport ranks for a wide class of metric spaces, followed by practical illustrations.

Bio Facts:

Dr. Chen, Assistant Professor at Rutgers University, holds a Ph.D. degree in statistics from the University of California, Davis, under the supervision of Dr. Hans-Georg Mueller. Her research interests are mainly in functional data analysis and non-Euclidean data analysis.