Table of Contents

A course on Markov Chains: Advanced topics

Registration to the course

Program of the course

Prof Chapters Topics Material Cours
1 (AD) Chapt. 1 and 2. Introduction to Markov chains, first definitions, Markov kernel, Elementary operations. Invariant measures / reversibility Exercise sheet 1 1
2 (AD) Chapt. 2 and 3 Canonical space. Kolmogorov extension theorem. Strong Markov property.Applications of the Markov properties: Stopping times. Exercise sheet 2 2
3 (AD) Dynamical systems, Birkhoff theorem
4 (AD) Chapt. 3 Metrics: TV norms, V norms, Wasserstein. Exercise sheet 3 3
Oct. 31 (RD) Chap 5 Geometric ergodicity. Chapitre 3 de ce polycopié 4/5
Nov 14 (RD) Chapt. 6 Central Limit Theorems 6
Nov 21 (RD) Chap 6 Rosenthal inequalities (Alain). 7
Nov 28 (AD) Chapt. 6-7-8 Quantitative Central Limit theorems 8
Dec 5 (RD) Chapt. 18-19 Convergence via spectral methods 9
Dec 12 (AD) Chap 21 Contractive convergence via curvature lower bounds. 10

Lecture notes Session 6-7-8-9

Example of an examination

Projects

Contact

name email adresses
Alain Durmus alain.durmus “Arobase” polytechnique.edu
Randal Douc randal.douc “Arobase” polytechnique.edu