PrerequisiteThe course addresses audience from different backgrounds in mathematics and theoretical physics. Only basic familiarity with algebra and representation theory as well as some elementary topology is assumed. No background in physics is formally required, but for appreciating the applications, a previous exposure to concepts of quantum mechanics and quantum field thepry will be of ava...
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...