Department of Mathematical Sciences, Ritsumeikan University Web Page

Date: 12 December (Thu)

Place: West Wing, 6th floor, Colloquium Room and on the Web (zoom)

Time: 16:30–18:00 

Speaker : Jorge Ignacio González Cázares (Universidad Nacional Autónoma de México)

Title: Markov Chain Monte Carlo: how and why? Ⅲ

Abstract: We will review classical and widely used Markov Chain Monte Carlo (MCMC) methods. We will begin by reviewing Markov Chain theory and posing the MCMC problem. We motivate the problem from the point of view of stochastic optimisation problems arising in statistics and machine learning. We introduce Metropolis Hastings and Gibbs samplers and show its simplicity using code. We will also hint at its connections with the popular SGD algorithm.