时间：2024年11月8日（星期五）14:00-16:00
地点：E10-212
主讲人: 哈尔滨工业大学，吴黎明
主讲人简介: Wu Liming, professor at Universite Clermont-Auvergne since 1993 and at HIT since 2021, is a probabilist working on large deviations, functional inequalities and stochastic analysis. He has worked also at Wuhan University， and Academy of Mathematics and Systems Sciences in Chinese Academy of Sciences.
讲座主题：Samplers of high dimensional Boltzmann distributions
讲座摘要: High dimensional Boltzmann distributions are basic models in statistical mechanics and in machine learning. However its computation is a NP-hard problem in the deterministic approaches: the curse of dimension.
In this talk I will present several current MCMC samplers such as Glauber dynamics, Gibbs samplers, and stochastic gradient descent. We will review some recent approaches for obtaining dimension-free estimates about the exponential convergence rate and the concentration inequalities, such as Poincare inequality, Gross' log-Sobolev inequality and Talagrand's transport inequality. Their applications in McKean-Vlasov equations and machine learning will be also presented.
