STAT 991-302: Mathematics of High-Dimensional Data

Course Description

This is a graduate level course covering various aspects of mathematical data science, particularly for large-scale problems. We will cover the mathematical foundations of several fundamental learning and inference problems, including spectral methods, tensor decomposition, matrix concentration inequalities, randomized linear algebra, sparse recovery and compressed sensing, low-rank matrix recovery, nonconvex matrix factorization, reinforcement learning, etc. We will focus on designing algorithms that are effective in both theory and practice.

Lectures

• Mon, Wed 1:45 PM - 3:15 PM

• Room:

  • Zoom: January 12 and January 19

  • F60, Jon M. Huntsman Hall: starting from January 24

Teaching Staffs

• Instructor: Yuxin Chen, 313 Academic Research Building, yuxinc at wharton dot upenn dot edu

Announcements

• 1/23: We have a new classroom: F60, Jon M. Huntsman Hall.