Convex Relative Entropy Decay in Markov Chains

by Prof. Venkat Anantharam (University of California, Berkeley, USA)

Tuesday 5 Aug 2014, 16:00 → 17:00 Asia/Kolkata

D-405 (D-Block Seminar Room) (Colaba Campus)

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).