応用数理
Online ISSN : 2432-1982
確率伝搬法の情報幾何 : 符号理論,統計物理,人工知能の接点
池田 思朗田中 利幸甘利 俊一
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2004 年 14 巻 3 号 p. 236-247

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Belief propagation is a universal method used in many field, such as AI, statistical physical, and error correction codes. It gives the exact inference when a graph is tree, but also a good approximation even if it is loopy. The authors have developed an information geometrical framework to analyze the belief propagation algorithm, which gives a unified view. In this article, the authors show the idea of the belief propagation algorithm, the information geometrical framework, and some results of the analysis.

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© 2004 一般社団法人 日本応用数理学会
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