How to Subscribe to the UCLA Statistics Seminars Mailing List
Join the UCLA Statistics seminars mailing list by sending an email to sympa@sympa.it.ucla.edu with “subscribe stat_seminars” (without quotation marks) in the subject field and the message body blank. This needs to be done from the address that is to be subscribed. After doing that please respond to the email that you receive. An automated email will be sent which confirms that you have been added.
How to Unsubscribe from the UCLA Statistics Seminars Mailing List
You may be receiving our seminar emails because you are directly subscribed to our seminars mailing list (or you may be one of our graduate students, undergraduate students, faculty, etc. and are subscribed to a different mailing list that also receives the seminar emails). If you are the former then you may unsubscribe from the seminar mailing list by sending an email to sympa@sympa.it.ucla.edu with “unsubscribe stat_seminars” (without quotation marks) in the subject field and the message body blank. This needs to be done from the address that is subscribed. After sending that email please follow the directions in the email response that you receive.
Viewing our Seminars Remotely
When viewing one of our live seminars remotely, it is optimal to have your Zoom settings such that you are using “Side-by-side: Speaker View”. You can see details of how to do this here.
Thursday 05/14/2026, Time: 2-3:15pm, Infinite-Order U-Processes and Their Applications to Half-Space Depth
Location: Public Affairs Building 1246
Stanislav Minsker, Professor
Department of Mathematics, University of Southern California
Abstract:
U-statistics were introduced by Wassily Hoeffding and Paul Halmos in the second half of the 1940s and have remained an active topic of research ever since. Estimation techniques based on U-statistics often yield highly efficient methods, which has been one of the main reasons for their success. U-processes are functional extensions of U-statistics and play a role similar to that of empirical processes in problems involving empirical risk minimization. Unlike empirical processes, however, U-processes are represented as sums of dependent terms, and this fact often creates challenges in their analysis.
While empirical processes admit sharp concentration bounds that pave the way for the analysis of many popular algorithms, similar guarantees for U-processes are lacking. We bridge this gap by presenting sharp deviation inequalities for U-processes, with a particular focus on their order. We then illustrate our results through applications to half-space depth. Specifically, we define a multivariate analogue of the Hodges–Lehmann estimator inspired by Tukey’s median and demonstrate an interesting phenomenon related to its asymptotic distribution.
This talk is based on joint work with Shunan Yao.
Bio:
Stanislav (Stas) Minsker is a Professor of Mathematics at USC. His research is focused on the problems related to robustness and statistics of high-dimensional data, as well as closely related probabilistic questions regarding the concentration-of-measure inequalities. He is a recipient of the National Science Foundation CAREER award.