E0 325: Probability and Statistics in High Dimensions, Fall 2017.

Instructors: Siddharth Barman and Arnab Bhattacharyya
Teaching Assistant: Suprovat Ghoshal.

Course Description
Many contemporary problems in data science require an understanding of high-dimensional statistics and probability to tackle the issues at hand. The goal of this course will be to give a tour through several mathematical phenomena that arise in high-dimensions and describe techniques to analyze them. Topics include concentration of measure, dimension reduction, restricted isometry, principal component analysis, and VC dimension, and applications to areas such as statistical inference (including linear regression and compressed sensing), empirical processes, and property testing.

Lectures are on every Tuesday and Thursday, 2 pm to 3:30 pm, at CSA 252. The first class is on Thursday, August 10.