Message passing for task redistribution on sparse graphs

K. Y Michael Wong*, David Saad, Zhuo Gao

*Corresponding author for this work

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

Abstract

The problem of resource allocation in sparse graphs with real variables is studied using methods of statistical physics. An efficient distributed algorithm is devised on the basis of insight gained from the analysis and is examined using numerical simulations, showing excellent performance and full agreement with the theoretical results.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems
Pages1529-1536
Number of pages8
Publication statusPublished - 1 Dec 2005
Event2005 Annual Conference on Neural Information Processing Systems, NIPS 2005 - Vancouver, BC, United Kingdom
Duration: 5 Dec 20058 Dec 2005

Conference

Conference2005 Annual Conference on Neural Information Processing Systems, NIPS 2005
CountryUnited Kingdom
CityVancouver, BC
Period5/12/058/12/05

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  • Cite this

    Wong, K. Y. M., Saad, D., & Gao, Z. (2005). Message passing for task redistribution on sparse graphs. In Advances in Neural Information Processing Systems (pp. 1529-1536)