Speaker：Hongxia Zhang（Suzhou University）

Time：2022-11-17, 10:00

Location：Tencent Meeting ID：875-723-167（No Password）

Abstract:

Some recent applications of multivariate statistical analysis in data science need to optimize certain trace-related objective functions over the orthogonal constraints. In this talk, we shall first present some recent applications in data science and show that solving the optimization problems can be converted to eigenvector-dependent eigenvalue problems (NEPv) for which the self-consistent filed (SCF) iteration can be effectively applied. We then discuss recent developments of the general SCF on the local convergence rate and the level-shifted technique.