Bayesian Network Inference Using Marginal Trees

被引：0

作者：

Butz, Cory J. ^{[1
]}

Oliveira, Jhonatan de S. ^{[2
]}

Madsen, Anders L. ^{[3
,4
]}

机构：

[1] Univ Regina, Dept Comp Sci, Regina, SK S4S 0A2, Canada

[2] Univ Fed Vicosa, Dept Elect Engn, BR-36570000 Vicosa, MG, Brazil

[3] Hugin Expert AS, DK-9000 Aalborg, Denmark

[4] Aalborg Univ, Dept Comp Sci, DK-9000 Aalborg, Denmark

来源：

PROBABILISTIC GRAPHICAL MODELS | 2014年 / 8754卷

关键词：

Bayesian network; inference; marginal trees; LAZY PROPAGATION;

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：

Variable Elimination (VE) answers a query posed to a Bayesian network (BN) by manipulating the conditional probability tables of the BN. Each successive query is answered in the same manner. In this paper, we present an inference algorithm that is aimed at maximizing the reuse of past computation but does not involve precomputation. Compared to VE and a variant of VE incorporating precomputation, our approach fairs favourably in preliminary experimental results.

引用

页码：81 / 96

页数：16

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