Description:High-dimensional statistical learning has become an increasingly important research area. In this course, we will provide theoretical foundations of high-dimensional learning for several widely studied problems with many applications. More specifically, we will review concentration inequalities, VC dimension, metric entropy and statistical implications, consider high-dimensional lin...
Speaker Daniel Litt is an Assistant Professor of mathematics at the University of Toronto. He was in a similar position at the University of Georgia from 2019-2022. He completed his PhD at Stanford in 2015; from 2015-2018 he was an NSF Postdoc at Columbia; and from 2018-2019 he was a member at the Institute for Advanced Study. Broadly speaking, he is interested in the interplay between algebrai...