Optimal bounded-degree approximations of joint distributions of networks of stochastic processes

Christopher J. Quinn, Ali Pinar, Negar Kiyavash

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publication2013 IEEE International Symposium on Information Theory, ISIT 2013
Pages2264-2268
Number of pages5
DOIs
StatePublished - Dec 19 2013
Event2013 IEEE International Symposium on Information Theory, ISIT 2013 - Istanbul, Turkey
Duration: Jul 7 2013Jul 12 2013

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Other

Other2013 IEEE International Symposium on Information Theory, ISIT 2013
Country/TerritoryTurkey
CityIstanbul
Period7/7/137/12/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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