favicon Frontiers in Mathematical Sciences
7th Conference
University of Isfahan - January 1-3, 2020
Modeling heterogeneity of high-dimensional data: A finite mixture model approach
Abbas Khalili, McGill University
Date, Time, and Venue:  Thursday, January 2 | 14:00-14:45 | Hall 2
Latent variable models such as finite mixtures provide flexible tools for modeling data from heterogeneous populations consisting of multiple hidden homogeneous sub-populations. In this talk, I will review some of the recent methodological developments for estimation and feature selection problems in finite mixture of regression models, as a supervised learning approach, toward analyzing high-dimensional data
University of Isfahan IPM-Isfahan National Elits Foundation Iran National Science Foundation