Convex Relative Entropy Decay in Markov Chains


Venkat Anantharam


University of California, Berkeley
Department of Electrical and
Computer Sciences
271, Coray Hall
Berkeley, CA 94720-1770
United States of America


Tuesday, 5 August 2014, 16:00 to 17:00



Abstract: Consider an irreducible continuous time Markov chain with a finite or a countably infinite number of states and admitting a unique stationary probability distribution. The relative entropy of the distribution of the chain at any time with respect to the stationary distribution is a monotonically decreasing function of time. It is interesting to ask if this function is convex. We discuss this question for finite Markov chains and for Jackson networks, which are a class of countable state Markov chains of interest in modelingnetworks of queues (joint work with Varun Jog).