High Dimensional Probability and Applications

Catalog description

In this course, we will introduce non-asymptotic methods in high-dimensional probability that find common use in applications across statistics, computer science, data science, and engineering. Topics include tail bounds for i.i.d. sums and martingale differences, concentration inequalities for non-linear functions, matrix concentration, and suprema of stochastic processes.