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置信度傳播

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置信度傳播(英語:belief propagation),又稱為乘積和信息傳遞sum-product message passing),是在貝葉斯網絡馬爾可夫隨機場概率圖模型中用於推斷的一種信息傳遞算法。在給定已觀測節點時,可以用該算法高效地計算未觀測節點的邊緣分佈。置信度傳播在人工智能信息論中十分常見,已成功應用於低密度奇偶檢查碼Turbo碼自由能估計、可滿足性英語Satisfiability等不同領域。[1]

置信度傳播由美國計算機科學家朱迪亞·珀爾於1982年提出。[2]最初該算法的運用範圍僅限於,不久則擴展到多樹英語Polytree[3]此後,研究者發現在一般的圖中該算法是一種十分有用的近似算法。[4]

參考文獻

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  1. ^ Braunstein, A.; Mézard, M.; Zecchina, R. Survey propagation: An algorithm for satisfiability. Random Structures & Algorithms. 2005, 27 (2): 201–226. doi:10.1002/rsa.20057. 
  2. ^ Pearl, Judea. Reverend Bayes on inference engines: A distributed hierarchical approach (PDF). Proceedings of the Second National Conference on Artificial Intelligence. AAAI-82: Pittsburgh, PA. Menlo Park, California: AAAI Press: 133–136. 1982 [2009-03-28]. (原始內容存檔 (PDF)於2011-06-04). 
  3. ^ Kim, Jin H.; Pearl, Judea. A computational model for combined causal and diagnostic reasoning in inference systems (PDF). Proceedings of the Eighth International Joint Conference on Artificial Intelligence. IJCAI-83: Karlsruhe, Germany 1: 190–193. 1983 [2016-03-20]. (原始內容存檔 (PDF)於2016-04-02). 
  4. ^ Pearl, Judea. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference 2nd. San Francisco, CA: Morgan Kaufmann. 1988. ISBN 1-55860-479-0. 

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