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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1783.1/2953
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| Title: | Message-passing for inference and optimization of real variables on sparse graphs |
| Authors: | Wong, Michael Kwok-Yee
Yeung, Chi Ho
Saad, David |
| Keywords: | Distributed algorithms
Graph theory
Message passing
Optimisation
Resource allocation
Statistical mechanics |
| Issue Date: | Oct-2006 |
| Citation: | Neural Information Processing. 13th International Conference, ICONIP 2006. Proceedings, Part II (Lecture notes in Computer Science Vol. 4233). Springer-Verlag. p. 754-63. Berlin, Germany |
| Abstract: | The inference and optimization in sparse graphs with real variables is studied using methods of statistical mechanics. Efficient distributed algorithms for the resource allocation problem are devised. Numerical simulations show excellent performance and full agreement with the theoretical results. |
| Rights: | This original publication is available at http://www.springerlink.com |
| URI: | http://hdl.handle.net/1783.1/2953 |
| Appears in Collections: | PHYS Conference Papers
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Files in This Item:
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| iconip_ra2.pdf | pre-published version | 263Kb | Adobe PDF | View/Open |
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