The dual polyhedron to the chordal graph polytope and the rebuttal of the chordal graph conjecture

DOI10.1016/j.ijar.2021.07.014OpenAlexW3198566902WikidataQ113872776 ScholiaQ113872776MaRDI QIDQ2060774

James Cussens, Milan Studený, Václav Kratochvíl

Publication date: 13 December 2021

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2021.07.014

zbMATH Keywords

learning decomposable modelschordal graph polytopeclutter inequalitiesdual polyhedron

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Cites Work

• A geometric view on learning Bayesian network structures
• Estimating the dimension of a model
• Learning Bayesian networks: The combination of knowledge and statistical data
• Polyhedral aspects of score equivalence in Bayesian network structure learning
• Characteristic imsets for learning Bayesian network structure
• Towards using the chordal graph polytope in learning decomposable models
• Learning Bayesian network structure: towards the essential graph by integer linear programming tools
• Learning Maximum Weighted (k+1)-Order Decomposable Graphs by Integer Linear Programming
• Probabilistic Networks and Expert Systems
• Lectures on Polytopes
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