DocumentCode
2003592
Title
Poset belief propagation-experimental results
Author
Harel, Jonathan ; Mceliece, Robert J. ; Palanki, Ravi
Author_Institution
Dept. of Electr. Eng., California Inst. of Technol., Pasadena, CA, USA
fYear
2003
fDate
29 June-4 July 2003
Firstpage
177
Abstract
Poset belief propagation, or PBP, is a flexible generalization of ordinary belief propagation which can be used to (approximately) solve many probabilistic inference problems. In this paper, we summarize some experimental results comparing the performance of PBP to conventional BP techniques.
Keywords
generalisation (artificial intelligence); inference mechanisms; belief propagation generalization; poset belief propagation; probabilistic inference problem; Belief propagation; Clustering algorithms; Damping; Inference algorithms; Information processing; Kernel; Performance gain; Probability density function; Sum product algorithm; Systems biology;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2003. Proceedings. IEEE International Symposium on
Print_ISBN
0-7803-7728-1
Type
conf
DOI
10.1109/ISIT.2003.1228191
Filename
1228191
Link To Document