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Zbl 1131.68510
Xie, Xianchao; Geng, Zhi; Zhao, Qiang
Decomposition of structural learning about directed acyclic graphs. (English)
[J] Artif. Intell. 170, No. 4-5, 422-439 (2006). ISSN 0004-3702

Summary: In this paper, we propose that structural learning of a directed acyclic graph can be decomposed into problems related to its decomposed subgraphs. The decomposition of structural learning requires conditional independencies, but it does not require that separators are complete undirected subgraphs. Domain or prior knowledge of conditional independencies can be utilized to facilitate the decomposition of structural learning. By decomposition, search for d-separators in a large network is localized to small subnetworks. Thus both the efficiency of structural learning and the power of conditional independence tests can be improved.

MSC 2000:: *68T05 Learning and adaptive systems

Keywords: Bayesian network; conditional independence; decomposition; directed acyclic graph; junction tree; structural learning; undirected graph

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