# STATS 200C: Large Sample Theory

**Prerequiste**: STATS 200A and B

Law of large number (L2 and L1 versions)

Central limit theorem (Characteristic function, Linderberg, Stein)

Large deviation and concentration inequalities (Chernoff, Cramer, Hoeffding, Benett, Bernstein)

Asymptotics of maximum likelihood and M-estimators, likelihood ratio test

Many means problem, minimax, Pinsker bound, Stein estimator, soft thresholding, oracle inequalities, theory of Lasso etc.

Supervised learning, VC dimension, Rademacher complexity, theories of SVM and adaboost.