All lecture notes

For Stanford affiliates, all lectures with notes are available in this folder

Overview

Overview (written)

Concentration and convergence

Concentration inequalities and tail bounds (written)

Uniform concentration inequalities, martingales, Rademacher complexity and symmetrization (written)

VC Dimension (written)

Metric entropy and chaining (written)

Fast rates of convergence for learning problems (written)

Convex optimization

Convex analysis background (written)

Subgradient methods (written)

Mirror descent and AdaGrad (written)

Online learning

Online learning and online convex optimization

Bandit problems

Kernels

Basics of Kernels