Selecting Reduced Models in the Cross-Entropy Method
نویسندگان
چکیده
منابع مشابه
The Cross-Entropy Method
This report is a summary of the theory underlying the Cross-Entropy (CE) method, as discussed in the tutorial by de Boer, Kroese, Mannor and Rubinstein [1]. For a more thorough discussion of the method and its applications, please refer to the original tutorial and the references cited in the tutorial. The CE method, pioneered by Rubinstein in 1997 as an adaptive algorithm for estimating probab...
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This chapter describes how difficult statistical estimation problems can often be solved efficiently by means of the cross-entropy (CE) method. The CE method can be viewed as an adaptive importance sampling procedure that uses the cross-entropy or Kullback–Leibler divergence as a measure of closeness between two sampling distributions. The CE method is particularly useful for the estimation of ...
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The cross-entropy (CE) method is a new generic approach to combinatorial and multi-extremal optimization and rare event simulation. The purpose of this tutorial is to give a gentle introduction to the CE method. We present the CE methodology, the basic algorithm and its modifications, and discuss applications in combinatorial optimization and machine learning.
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Cross-entropy optimization (CE) has proven to be a powerful tool for search in control environments. In the basic scheme, a distribution over proposed solutions is repeatedly adapted by evaluating a sample of solutions and refocusing the distribution on a percentage of those with the highest scores. We show that, in the kind of noisy evaluation environments that are common in decisionmaking dom...
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ژورنال
عنوان ژورنال: SIAM/ASA Journal on Uncertainty Quantification
سال: 2020
ISSN: 2166-2525
DOI: 10.1137/18m1192500