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arXiv 1206.3241cs.LGstat.ML
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通过删除然后校正模型边缘来近似配分函数

Approximating the Partition Function by Deleting and then Correcting for Model Edges

University of California, Los Angeles(加利福尼亚大学洛杉矶分校)

Arthur Choi, Adnan Darwiche

摘要:

我们提出了一种方法来近似的分区函数,这是基于两个步骤:(1)计算分区函数的简化模型,这是通过删除模型的边缘,(2)纠正的结果,通过应用边缘边缘的校正。该方法导致一个直观的框架,其中可以权衡的质量近似计算的复杂性。它还包括贝特自由能近似作为一个退化的情况下。我们在本文中理论上开发的方法,并提供了一些实证结果,揭示其实际效用。

英文摘要:

We propose an approach for approximating the partition function which is based on two steps: (1) computing the partition function of a simplified model which is obtained by deleting model edges, and (2) rectifying the result by applying an edge-by-edge correction. The approach leads to an intuitive framework in which one can trade-off the quality of an approximation with the complexity of computing it. It also includes the Bethe free energy approximation as a degenerate case. We develop the approach theoretically in this paper and provide a number of empirical results that reveal its practical utility.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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