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

Author

Quinn, Christopher J. ; Pinar, Ali ; Kiyavash, Negar

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Illinois, Urbana, IL, USA

fYear

2013

fDate

7-12 July 2013

Firstpage

2264

Lastpage

2268

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.

Keywords

directed graphs; stochastic processes; KL divergence; bounded indegree; directed graphs; low-complexity network structures; near-optimality; optimal bounded-degree approximations; stochastic processes; Approximation algorithms; Approximation methods; Complexity theory; Greedy algorithms; Information theory; Joints; Optimized production technology;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on

Conference_Location

Istanbul

ISSN

2157-8095

Type

conf

DOI

10.1109/ISIT.2013.6620629

Filename

6620629

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=640289