High Dimensions, Inference and Combinatorics. A
Journey Through the Data Jungle
This talk takes us on a journey through modern high-dimensional statistics. We begin with a brief discussion on variable selection and estimation and the challenges they bring to high-dimensional inference, and we formulate a new family of inferential problems
for graphical models. Our aim is to conduct hypothesis tests on graph properties such as connectivity, maximum degree and cycle presence. The testing algorithms we introduce are applicable to properties which are invariant under edge addition. In parallel, we also develop a minimax lower bound showing the
optimality of our tests over a broad family of graph properties. We apply our methods to study neuroimaging data.
Friday, January 13, 2017
11:00 AM to 12:00 PM
Keck Hall, RM102