STAT 903 - High-Dimensional Probability

An introductory course in high-dimensional probability and its applications. Topics will include: the concentration of measure phenomenon, isoperimetric and functional inequalities, and asymptotic and non-asymptotic random matrix theory. Applications may include empirical processes, dimension reduction, sparse models including compressed sensing, BBP transitions and high-dimensional PCA, mean-field methods, and optimization in high-dimensions.