首页> 外文会议>International Symposium on Computer and Information Sciences(ISCIS 2005); 20051026-28; Istanbul(TR) >An Alternative Proof That Exact Inference Problem in Bayesian Belief Networks Is NP-Hard
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An Alternative Proof That Exact Inference Problem in Bayesian Belief Networks Is NP-Hard

机译:贝叶斯信念网络中确切推理问题的另一种证明是NP-Hard

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摘要

Exact inference problem in belief networks has been well studied in the literature and has various application areas. It is known that this problem and its approximation version are NP-hard. In this study, an alternative polynomial time transformation is provided from the well-known vertex cover problem. This new transformation may lead to new insights and polynomially solvable classes of the exact inference problem in Bayesian belief networks.
机译:信念网络中的精确推理问题已经在文献中进行了深入研究,并具有各种应用领域。已知此问题及其近似形式是NP-hard。在这项研究中,从众所周知的顶点覆盖问题中提供了另一种多项式时间变换。这种新的转变可能导致贝叶斯信念网络中确切推理问题的新见解和多项式可解类。

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