A0872
Title: Scaling limit of Markov chain/process Monte Carlo methods
Authors: Kengo Kamatani - ISM (Japan) [presenting]
Abstract: The scaling limit analysis of Markov Chain Monte Carlo methods has been a topic of intensive study in recent decades. The analysis determines the rate at which the Markov Chain converges to its limiting process, typically a Langevin diffusion process, and provides valuable guidelines for parameter tuning. Numerous researchers have generalized the original assumptions and expanded the results to more sophisticated methods. Recently, there has been growing interest in piecewise deterministic Markov processes for Monte Carlo integration methods, particularly the Bouncy Particle Sampler and the Zig-Zag Sampler. The method focuses on determining the scaling limits for both algorithms and provides a criterion for tuning the Bouncy Particle Sampler.
