Zhaojun Bai: Rayleigh quotient optimizations and eigenvalue problems
Tid: On 2019-10-23 kl 11.45 - 12.30
Plats: 306, kräftriket
Föreläsare: Zhaojun Bai, University of California, Davis
Many computational science and data analysis techniques lead to optimizing Rayleigh quotient (RQ) and RQ type objective functions, such as computing excitation states (energies) of electronic structures, robust classification to handle uncertainty and constrained data clustering to incorporate a prior information. We will discuss origins of recently emerging RQ optimization problem, variational principles, and reformulations to algebraic linear and nonlinear eigenvalue problems. We will show how to exploit underlying properties of eigenvalue problems for designing eigensolvers, and illustrate the efficacy of these solvers in applications.