ELE520: Mathematics of Data Science

Yuxin Chen, Princeton University, Fall 2020
alt text 

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 clustering, spectral methods, tensor decomposition, graphical models, large-scale numerical linear algebra, matrix concentration inequalities, sparse recovery and compressed sensing, low-rank matrix recovery, shallow neural nets, etc. Both convex and nonconvex approaches will be discussed. We will focus on designing algorithms that are effective in both theory and practice.


  • Tue, Thu 9:30 AM - 10:50 AM

Teaching Staffs

  • Instructor: Yuxin Chen, C330 Equad, yuxin dot chen at princeton dot edu

  • Teaching assistant: