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ADVANCES IN CROSS-ENTROPY METHODS

Part of: Inference from stochastic processes Probabilistic methods, simulation and stochastic differential equations Algorithms - Computer Science

Published online by Cambridge University Press:  02 October 2009

THOMAS TAIMRE
THOMAS TAIMRE*
Affiliation:
School of Mathematics and Physics, The University of Queensland, Brisbane 4072, Australia (email: [email protected])
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Abstract

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Keywords

cross-entropyimportance samplingrare eventsoptimization

MSC classification

Secondary: 65C05: Monte Carlo methods 90C27: Combinatorial optimization 68W20: Randomized algorithms 62M05: Markov processes
Type
PhD thesis
Information
Bulletin of the Australian Mathematical Society , Volume 80 , Issue 3 , December 2009 , pp. 521 - 522
Copyright
Copyright © Australian Mathematical Publishing Association Inc. 2009

References

[1]Rubinstein, R. Y., ‘Optimization of computer simulation models with rare events’, European J. Oper. Res. 99 (1997), 89–112.CrossRefGoogle Scholar
[2]Rubinstein, R. Y., ‘The cross-entropy method for combinatorial and continuous optimization’, Methodol. Comput. Appl. Probab. 1 (1999), 127–190.CrossRefGoogle Scholar
[3]Rubinstein, R. Y. and Kroese, D. P., The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation, and Machine Learning (Springer, New York, 2004).CrossRefGoogle Scholar