SDS 384-11:Theoretical Statistics
While measure theory is not a pre-requisite for this class, you can use Peter Hoff's notes on measure theory if needed. Another excellent reference is ``Probability and Measure''
01/15,17 : Syllabus [PDF] , and stochastic convergence [Slides].
01/12,17 : More stochastic convergence [Slides]. Chapter 2 Van-der-vaart
01/31, 2/1 : Concentration inequalities I (Markov, Chebychev, Hoeffding's Lemma, SubGaussian RVs) [Slides].
02/1 : Concentration inequalities II (Subexponential RV's, JL Lemma) [Slides].
02/1,6 : Concentration inequalities III (Martingales, Azuma-Hoeffding, McDiarmid's inequality) [Slides].
02/6,8 : Concentration inequalities III (The Gaussian Lipschitz theorem) [Slides].
02/13,18 : Concentration inequalities IV (Talagrand's inequality) [Slides].
Reading : Terry Tao's notes for Talagrand's inequality [Here].
Reading : The USVT paper by Sourav Chatterjee [Here].
02/20 : Efron-Stein inequality [Slides].
Reading : Chapter 4 from Gabor Lugosi's notes [here].