Learning Bounded Tree-Width Bayesian Networks via Sampling

DOI10.1007/978-3-319-20807-7_35zbMath1465.68226OpenAlexW2398232135MaRDI QIDQ3451198

Siqi Nie, Cassio Polpo de Campos, Qiang Ji

Publication date: 10 November 2015

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-20807-7_35

zbMATH Keywords

Bayesian networkstructure learningbounded tree-width

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Probabilistic graphical models (62H22)

Related Items (4)

Efficient learning of Bayesian networks with bounded tree-width ⋮ Optimization problems for machine learning: a survey ⋮ Approximate structure learning for large Bayesian networks ⋮ Efficient learning of bounded-treewidth Bayesian networks from complete and incomplete data sets

Uses Software

• UCI-ml

Cites Work

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• Bijective linear time coding and decoding for \(k\)-trees
• A Bayesian method for the induction of probabilistic networks from data
• Estimating the dimension of a model
• Learning Bayesian networks: The combination of knowledge and statistical data
• The Necessity of Bounded Treewidth for Efficient Inference in Bayesian Networks
• Complexity of Finding Embeddings in a k-Tree

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