报告人：王凤雨 教授（天津大学）

时间：2026年06月16日 09:00-

地点：理科楼LA103

摘要：To derive dimension-free convergence rates of empirical measures for Markov processes on a Banach space, we use the sliced Wasserstein distance (SW distance) induced by a probability measure with full support on the unit ball of the dual space. This distance is topologically stronger than the convergence in finite-dimensional distributions, and is equivalent to the Wasserstein distance in the finite-dimensional case.  Under this distance, we present dimension-free convergence rates  for the empirical measures of ergodic Markov processes, which can be sharp as illustrated by concrete examples.

邀请人：周国立

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