Tata Institute of Fundamental Research
Convex Relative Entropy Decay in Markov Chains
Seminar
Speaker:
Venkat Anantharam (University of California, Berkeley
Department of Electrical and
Computer Sciences
271, Coray Hall
Berkeley, CA 94720-1770
United States of America)
Organiser:
Sandeep K Juneja
Date:
Tuesday, 5 Aug 2014, 16:00 to 17:00
Venue:
D-405 (D-Block Seminar Room)
(Scan to add to calendar)
Abstract:
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).
| Speaker: | Venkat Anantharam (University of California, Berkeley Department of Electrical and Computer Sciences 271, Coray Hall Berkeley, CA 94720-1770 United States of America) |
| Organiser: | Sandeep K Juneja |
| Date: | Tuesday, 5 Aug 2014, 16:00 to 17:00 |
| Venue: | D-405 (D-Block Seminar Room) |
(Scan to add to calendar)
Abstract:
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).