The following schedule is based on Japanese standard time.
Date: 2nd March
Time: 15:00 - 16:00 JST
In person location: Seminar Room B, Building No. 6, Faculty of Engineering, Hongo Campus, University of Tokyo
Speaker: Jeffrey S. Rosenthal, University of Toronto
Title: Optimising MCMC Tempering Algorithms
Abstract: Markov chain Monte Carlo (MCMC) algorithms are very popular in Bayesian statistics, but have difficulties moving between widely separated modes of the target distribution. A common solution is Simulated or Parallel Tempering algorithms, which use fractional powers of the target density to facilitate inter-mode transitions. This leads to questions about what choices to make re temperature spacings, balancing within- and between-temperature updates, and using reversible or non-reversible update schemes. In this talk, we present some theoretical results about how to optimise these choices to maximise the efficiency of the algorithm.
オンライン参加希望の方はフォームに登録をお願いします．If you plan to attend online, kindly register by using the link:
Virtual: https://us06web.zoom.us/meeting/register/kzv95m3USX63091LfJ-Q1A