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A differential semantics for jointree algorithms
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DOI：10.1016/j.artint.2003.04.004.png)
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摘要
En 中文
A new approach to inference in belief networks has been recently proposed, which is based on an algebraic representation of belief networks using multi-linear functions. According to this approach, belief network inference reduces to a simple process of evaluating and differentiating multi-linear functions. We show here that mainstream inference algorithms based on jointrees are a special case of the approach based on multi-linear functions, in a very precise sense. We use this result to prove new properties of jointree algorithms. We also discuss some practical and theoretical implications of this new finding. (C) 2004 Elsevier B.V. All rights reserved.
Keyword:
Bayesian networks
jointrees
arithmetic circuits
partial derivatives
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