Markov Chains: Reversibility & Convergence

This lecture covers the concepts of Markov chains, focusing on reversibility and convergence. Topics include discrete state Markov chains, Metropolis-Hastings algorithm, and the general state space of Markov chains. The instructor explains the properties of reversible Markov chains and discusses the exponential convergence of Markov chains. Additionally, the lecture delves into ergodicity, geometric ergodicity, and the convergence of Markov chains. The presentation concludes with detailed explanations of the convergence properties of Markov chains and their applications.