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