DocumentCode :
120737
Title :
Ordering strategies for removing redundant fill edges
Author :
Zhengwu Yang ; Hong Huo ; Tao Fang
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
fYear :
2014
fDate :
21-22 Feb. 2014
Firstpage :
744
Lastpage :
753
Abstract :
Triangulation is the key step for determining the maximum size of cliques, by which the performances of probabilistic inference algorithms are determined. Obtaining the optimal triangulation is NP-complete. But, triangulation performance can be improved through removing redundant fill edges from the triangulated graph. MinimalChordal and Recursive-Thinning are two popular methods for removing redundant fill edges. It has been validated that if the triangulated graph is minimal, the number of fill edges removed by them is small. In this paper, we shall analyze ordering strategies related to their performance, and propose two ordering algorithms for improving them. However, their performances are determined by triangulation orderings. To make them valuable, some better triangulation ordering method similar to MCS-M is expected even if it is not minimal.
Keywords :
computational complexity; graph theory; probability; MinimalChordal method; NP-complete problem; Recursive-Thinning method; ordering algorithms; ordering strategies; probabilistic inference algorithms; redundant fill edge removal; triangulated graph; triangulation ordering method; triangulation performance; Automation; Conferences; Control systems; Educational institutions; Inference algorithms; Information processing; Probabilistic logic; MinimalChordal; Ordering Strategies; Probabilistic Graphic Model; Recursive-Thinning; Redundant fill edges;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advance Computing Conference (IACC), 2014 IEEE International
Conference_Location :
Gurgaon
Print_ISBN :
978-1-4799-2571-1
Type :
conf
DOI :
10.1109/IAdCC.2014.6779417
Filename :
6779417
Link To Document :
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