Bidirectional Heuristic Search for Bayesian Network Structure with Ancestral Partition

Xiangyuan Tan, Xiaoguang Gao, Zidong Wang, Xiaohan Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Exact algorithms for learning optimal Bayesian networks require much more time and are used in small Bayesian networks. This paper adds ancestral partition constraints into the bidirectional heuristic search algorithm based on the order graph. The ancestral partition can be obtained by extracting strongly connected components from possible parent sets. Experiments show that ancestral partition can significantly improve the efficiency and scalability of bidirectional heuristic search. In addition, with ancestral partition constraints, bidirectional heuristic search has better efficiency and can search larger Bayesian networks than state-of-the-art algorithms.

Original languageEnglish
Title of host publication2022 7th International Conference on Control and Robotics Engineering, ICCRE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages111-116
Number of pages6
ISBN (Electronic)9781665468404
DOIs
StatePublished - 2022
Event7th International Conference on Control and Robotics Engineering, ICCRE 2022 - Beijing, China
Duration: 15 Apr 202217 Apr 2022

Publication series

Name2022 7th International Conference on Control and Robotics Engineering, ICCRE 2022

Conference

Conference7th International Conference on Control and Robotics Engineering, ICCRE 2022
Country/TerritoryChina
CityBeijing
Period15/04/2217/04/22

Keywords

  • Bayesian network
  • order graph
  • structure learning

Fingerprint

Dive into the research topics of 'Bidirectional Heuristic Search for Bayesian Network Structure with Ancestral Partition'. Together they form a unique fingerprint.

Cite this