Rayleigh quotient optimizations and eigenvalue problems (Zhaojun Bai - University of California, Davis)

28.03.2017 15:15 – 16:00

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. In this talk, we will discuss origins of RQ optimizations, variational principles, and reformulations to algebraic eigenvalue problems. We will show how to exploit underlying properties of eigenvalue problems for design reliable and fast eigensolvers, and illustrate the efficacy of these eigensolvers in electronic structure calculations and constrained image segmentation.

Lieu

salle 624, Séminaire d'analyse numérique

entrée libre