Title: Entropy-based convergence rates of greedy algorithms

Time: 16:00--17:00 on September 11, 2024

Meeting Room: Math Building 2-3 Room

Speaker: Yuwen Li, Zhejiang University

Abstract: Greedy algorithms are ubiquitous in computational mathematics. In this talk, I will present novel convergence estimates of greedy algorithms including the reduced basis method for parametrized PDEs, the empirical interpolation method for approximating parametric functions, and the orthogonal/Chebyshev greedy algorithms for nonlinear dictionary approximation. The proposed convergence rates are all based on the metric entropy of underlying compact sets. This talk is partially based on joint work Jonathan Siegel.

Introduction: Dr. Yuwen Li received a bachelor's and master's degree from Nanjing University and a PhD in mathematics from University of California San Diego. He was a S. Chowla Assistant Research Professor at Penn State from 2019-2022. After that he became a faculty member of school of mathematical sciences at Zhejiang University. His main research areas include finite element methods, adaptive algorithms, iterative solvers etc. His research results have been published in SINUM, MathComp, FoCM, M3AS, IMANUM, SISC, JCP etc.