Foundation of Data Science

Schedule: 

•      8:30–10AM: Basics of Machine Learning Theory by Vinodchandran Variyam
•      10:15–11:45: High-Dimensional Probability Foundations for Statistical Machine Learning (a.k.a. Non-asymptotic Random Matrix Theory) by Namrata Vaswani
•      11:45–1PM: Lunch
•      1PM—2:30PM: A Tutorial on Robust Methods for Structured Data Problems by Gilad Lerman
•      2:45–4:15PM: A Practical Introduction to Topological Data Analysis by Michael Catanzaro