• CS 5150/6150: Graduate Algorithms. I usually teach this course in the fall. The course is meant to be an introductory algorithms class for graduate students. Students signing up are expected to have done an undergrad level data structures/algorithms class, and are expected to be comfortable with discrete mathematics. Here is a link to the Fall 2019 homepage. You will find links to the course content, lecture notes and lecture videos (on Youtube).

  • Theory of Machine Learning It has been a couple of years since I taught this course. But take a look at the course home page for pointers to the material.

  • Techniques in Algorithms and Approximation. This is a graduate level course covering approximation algorithms, spectral methods, hardness, etc. It is accessible to students comfortable with the material in CS 6150. (Course page)

  • Fall 2016: ML Seminar: Large scale machine learning. (Course page)