TY - GEN
T1 - Optimal bounded-degree approximations of joint distributions of networks of stochastic processes
AU - Quinn, Christopher J.
AU - Pinar, Ali
AU - Kiyavash, Negar
PY - 2013/12/19
Y1 - 2013/12/19
N2 - We propose two algorithms to identify approximations for joint distributions of networks of stochastic processes. The approximations correspond to low-complexity network structures - connected, directed graphs with bounded indegree. The first algorithm identifies an optimal approximation in terms of KL divergence. The second efficiently finds a near-optimal approximation. Sufficient conditions are introduced to guarantee near-optimality.
AB - We propose two algorithms to identify approximations for joint distributions of networks of stochastic processes. The approximations correspond to low-complexity network structures - connected, directed graphs with bounded indegree. The first algorithm identifies an optimal approximation in terms of KL divergence. The second efficiently finds a near-optimal approximation. Sufficient conditions are introduced to guarantee near-optimality.
UR - http://www.scopus.com/inward/record.url?scp=84890329339&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890329339&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2013.6620629
DO - 10.1109/ISIT.2013.6620629
M3 - Conference contribution
AN - SCOPUS:84890329339
SN - 9781479904464
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2264
EP - 2268
BT - 2013 IEEE International Symposium on Information Theory, ISIT 2013
T2 - 2013 IEEE International Symposium on Information Theory, ISIT 2013
Y2 - 7 July 2013 through 12 July 2013
ER -