On Polyhedral Approximations of Polytopes for Learning Bayesian Networks

DOI10.18409/jas.v4i1.19zbMath1353.90091OpenAlexW2137651751MaRDI QIDQ2819996

David C. Haws, Milan Studený

Publication date: 13 September 2016

Published in: Journal of Algebraic Statistics (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/f417a540bd4c04463dbc21da28630536b69d36eb

zbMATH Keywords

integer programmingLP relaxationstandard imsetBayesian network structure learningcharacteristic imset

Mathematics Subject Classification ID

Multivariate analysis (62H99) Integer programming (90C10) Graph theory (including graph drawing) in computer science (68R10) Matrices of integers (15B36)

Related Items (5)

Polyhedral aspects of score equivalence in Bayesian network structure learning ⋮ Exact estimation of multiple directed acyclic graphs ⋮ Towards using the chordal graph polytope in learning decomposable models ⋮ Learning Bayesian network structure: towards the essential graph by integer linear programming tools ⋮ Polyhedral approaches to learning Bayesian networks

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