Teaching

Prof. Gavin Brown and me have written a ~100 page book on introducing statistical learning theory to CS undergrads. The plan is to teach this book in 12 weeks. Between weeks 7 to 12, I will teach an introduction to optimization theory, proof of implicit bias in over-parameterized linear regression, proof of bounding generalization error by Rademacher complexity and basic examples of computing Rademacher complexity bounds like Massart's Lemma and for linear functions.

As a part of this course I taught a hands-on introduction to Variational Auto-Encoders - which was more than 50% of the final grade.