置信度傳播
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、馬爾可夫隨機場等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布。置信度傳播在人工智慧、資訊理論中十分常見，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樹，不久則擴展到多樹。[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
- ^ 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.
- ^ 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）.
- ^ 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）.
- ^ Pearl, Judea. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference 2nd. San Francisco, CA: Morgan Kaufmann. 1988. ISBN 1-55860-479-0.
延伸閱讀
- Bickson, Danny. (2009). Gaussian Belief Propagation Resource Page （頁面存檔備份，存於網際網路檔案館） —Webpage containing recent publications as well as Matlab source code.
- Bishop, Christopher M. Chapter 8: Graphical models (PDF). Pattern Recognition and Machine Learning. Springer. 2006: 359–418 [2014-03-20]. ISBN 0-387-31073-8. （原始內容存檔 (PDF)於2016-03-20）.
- Coughlan, James. (2009). A Tutorial Introduction to Belief Propagation.
- Koch, Volker M. (2007). A Factor Graph Approach to Model-Based Signal Separation —A tutorial-style dissertation
- Löliger, Hans-Andrea. An Introduction to Factor Graphs. IEEE Signal Proc. Mag. 2004, 21: 28–41 [2017-10-19]. （原始內容存檔於2017-05-17）.
- Mackenzie, Dana (2005). "Communication Speed Nears Terminal Velocity （頁面存檔備份，存於網際網路檔案館）", New Scientist. 9 July 2005. Issue 2507 (Registration required)
- Wymeersch, Henk. Iterative Receiver Design. Cambridge University Press. 2007 [2017-10-19]. ISBN 0-521-87315-0. （原始內容存檔於2016-03-03）.
- Yedidia, J.S.; Freeman, W.T.; Weiss, Y. Understanding Belief Propagation and Its Generalizations. Lakemeyer, Gerhard; Nebel, Bernhard (編). Exploring Artificial Intelligence in the New Millennium. Morgan Kaufmann. January 2003: 239–236 [2009-03-30]. ISBN 1-55860-811-7. （原始內容存檔於2020-12-05）.
- Yedidia, J.S.; Freeman, W.T.; Weiss, Y. Constructing free-energy approximations and generalized belief propagation algorithms. IEEE Transactions on Information Theory. July 2005, 51 (7): 2282–2312 [2009-03-28]. doi:10.1109/TIT.2005.850085. （原始內容存檔於2009-04-18）.