Title: Transelliptical Graphical Models: Theory and Computation
Abstract: We introduce the theory and computation of a semiparametric approach for estimating high dimensional graphical models. There are two main themes of this talk: semiparametric sparsity and statistical optimization. We illustrate the concept of semiparametric sparsity through the transelliptical graphical modeling, and illustrate the concept of statistical optimization through the theoretical analysis of a pathwise coordinate optimization algorithm named PICASA.
(Random Matrix and Probability Theory seminar: flyer)