• 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