On the Structure of Elimination Trees for Bayesian Network Inference

被引：0

作者：

Grant, Kevin ^{[1
]}

Scholten, Keilan ^{[1
]}

机构：

[1] Univ Lethbridge, Dept Math & Comp Sci, Lethbridge, AB T1K 3M4, Canada

来源：

ADVANCES IN SOFT COMPUTING - MICAI 2010, PT II | 2010年 / 6438卷

关键词：

Bayesian networks; inference; offline computation;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present an optimization to elimination tree inference in Bayesian networks through the use of unlabeled nodes, or nodes that are not labeled with a variable from the Bayesian network. Through the use of these unlabeled nodes, we are able to restructure these trees, and reduce the amount of computation performed during the inference process. Empirical tests show that the algorithm can reduce multiplications by up to 70%, and overall runtime by up to 50%.

引用

页码：208 / 220

页数：13

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