论文标题
马尔可夫连锁店的庞加莱不平等：与Cheeger，Lyapunov和Metropolis会面
Poincaré inequalities for Markov chains: a meeting with Cheeger, Lyapunov and Metropolis
论文作者
论文摘要
我们开发了一种薄弱的庞加莱不平等的理论，以表征千古马尔可夫链的收敛速率。由马尔可夫连锁店在算法的背景下应用的动机，我们开发了一组相关的工具，使马尔可夫链蒙特卡洛方法的融合速率可以实践研究，但也远远超出了。
We develop a theory of weak Poincaré inequalities to characterize convergence rates of ergodic Markov chains. Motivated by the application of Markov chains in the context of algorithms, we develop a relevant set of tools which enable the practical study of convergence rates in the setting of Markov chain Monte Carlo methods, but also well beyond.
