Signal recovery, restriction theory and real-life applications

When

November 3rd, 2025 | 2:30 p.m. – 3:30 p.m.
Refreshments provided at 2:00 in lobby

Where

University Hall 1005

Speaker

Alex Iosevich, University of Rochester

Abstract

One of the most important and basic problems in data analytics is to accurately impute the values of a time series. In this talk, we are going to focus on developing the exact signal recovery tools to perform this imputation. In the process, we are going to describe some intriguing connections between signal recovery, time series imputation, and some classical problems in harmonic analysis, such as restriction theory, the Bourgain/Talagrand theory of orthogonal functions, and random polynomial approximation. The talk is designed to be accessible to a broad mathematical audience.

*The talk will be focused on and accessible to graduate students. All are encouraged to attend.