报告题目：Rayleigh quotient optimizations and eigenvalue problems
报告人：Zhaojun Bai(柏兆俊), Professor, University of California, Davis
报告时间：2017年12月21日10:30
报告地点：18-918
报告摘要：Many computational science and data analysis techniques lead tooptimizingRayleigh-Quotient (RQ) and RQ-type objective functions,such as computing excitation states (energies) of electronic structures,robust classification to handle uncertainty and constraineddata clustering to incorporate a prior information. In this talk,we will discuss origins of some RQ optimizations, variational principles,and reformulations to algebraic linear and nonlinear eigenvalue problems.We will show how to exploit underlying properties of eigenvalue problemsfor designing eigensolvers, and illustrate the efficacy ofthese solvers in electronic structure calculations and constrainedimage segmentation.
主讲人简介：（Speaker biosketch）
Zhaojun Bai is a Professor in the Department of Computer Science and Department of Mathematics, University of California, Davis. He obtainedhis PhD from Fudan University, China and post-doctorial fellowshipfrom Courant Institute, New York University. His main research interests include linear algebra algorithm design and analysis, high-performancemathematical software engineering and applications in computationalscience and engineering. He participated a number of large scale
synergistic projects, such as LAPACK. He serves on editorial boards of ACM TOMS, JCM, and Science China Mathematics. Previously, he has served as an associateeditor of SIMAX, and vice chair of IEEE IPDPS andnumerous other profession alpositions. He is a Fellow of SIAM.
