Presentation | 2008-01-15 Analytical and Numerical Solutions of Bethe Approximation in Normal Distributions Yu NISHIYAMA, Sumio WATANABE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | For the calculation of marginal distributions, which require the huge computational cost, the algorithm called belief propagation(BP) has shown the effectiveness. Loopy belief propagation(LBP), which is the BP applied to the distributions that have loops, is not guaranteed to converge in general and, if it converges, it computes approximate marginal probabilities. The LBP fixed-points after the convergence are also given by the extrema of the evaluation function called Bethe free energy. In this paper, we clarify the extrema of Bethe free energy in some particular cases of normal distributions, and after we give the convergence condition of LBP and the accuracy of LBP, we do the numerical experiments and compare the results with analytical solutions. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Bethe Approximation / Bethe Free Energy / Loopy Belief Propagation / Single Cycle |
Paper # | NC2007-87 |
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Committee | NC |
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Conference Date | 2008/1/8(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Analytical and Numerical Solutions of Bethe Approximation in Normal Distributions |
Sub Title (in English) | |
Keyword(1) | Bethe Approximation |
Keyword(2) | Bethe Free Energy |
Keyword(3) | Loopy Belief Propagation |
Keyword(4) | Single Cycle |
1st Author's Name | Yu NISHIYAMA |
1st Author's Affiliation | Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology() |
2nd Author's Name | Sumio WATANABE |
2nd Author's Affiliation | Precision and Intelligence Laboratory, Tokyo Institute of Technology |
Date | 2008-01-15 |
Paper # | NC2007-87 |
Volume (vol) | vol.107 |
Number (no) | 413 |
Page | pp.pp.- |
#Pages | 6 |
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