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The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning (Information Science and Statistics)

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The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning (Information Science and Statistics) Cover

 

Synopses & Reviews

Publisher Comments:

The cross-entropy (CE) method is one of the most significant developments in stochastic optimization and simulation in recent years. This book explains in detail how and why the CE method works. The CE method involves an iterative procedure where each iteration can be broken down into two phases: (a) generate a random data sample (trajectories, vectors, etc.) according to a specified mechanism; (b) update the parameters of the random mechanism based on this data in order to produce a ``better sample in the next iteration. The simplicity and versatility of the method is illustrated via a diverse collection of optimization and estimation problems. The book is aimed at a broad audience of engineers, computer scientists, mathematicians, statisticians and in general anyone, theorist or practitioner, who is interested in fast simulation, including rare-event probability estimation, efficient combinatorial and continuous multi-extremal optimization, and machine learning algorithms. Reuven Y. Rubinstein is the Milford Bohm Professor of Management at the Faculty of Industrial Engineering and Management at the Technion (Israel Institute of Technology). His primary areas of interest are stochastic modelling, applied probability, and simulation. He has written over 100 articles and has published five books. He is the pioneer of the well-known score-function and cross-entropy methods. Dirk P. Kroese is an expert on the cross-entropy method. He has published close to 40 papers in a wide range of subjects in applied probability and simulation. He is on the editorial board of Methodology and Computing in Applied Probability and is Guest Editor of the Annals of Operations Research. He has held research and teaching positions at Princeton University and The University of Melbourne, and is currently working at the Department of Mathematics of The University of Queensland. "Rarely have I seen such a dense and straight to the point pedagogical monograph on such a modern subject. This excellent book, on the simulated cross-entropy method (CEM) pioneered by one of the authors (Rubinstein), is very well written..." Computing Reviews, Stochastic Programming November, 2004 "It is a substantial contribution to stochastic optimization and more generally to the stochastic numerical methods theory." Short Book Reviews of the ISI, April 2005 "...I wholeheartedly recommend this book to anybody who is interested in stochastic optimization or simulation-based performance analysis of stochastic systems." Gazette of the Australian Mathematical Society, vol. 32 (3) 2005

Synopsis:

Rubinstein is the pioneer of the well-known score function and cross-entropy methods. Accessible to a broad audience of engineers, computer scientists, mathematicians, statisticians and in general anyone, theorist and practitioner, who is interested in smart simulation, fast optimization, learning algorithms, and image processing.

Table of Contents

Preliminaries * A Tutorial Introduction to the Cross-Entropy Method * Efficient Simulation via Cross-Entropy * Combinatorial Optimization via Cross-Entropy * Continuous Optimization and Modifications * Noisy Optimization with CE *Applications of CE to COPs * Applications of CE to Machine Learning *Appendix: Example Programs

Product Details

ISBN:
9781441919403
Author:
Rubinstein, Reuven Y.
Publisher:
Springer
Author:
Kroese, Dirk P.
Location:
New York, NY
Subject:
Simulation and Modeling
Subject:
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Subject:
Operations Research/Decision Theory
Subject:
Probability and Statistics in Computer Science
Subject:
Computational intelligence
Subject:
Operations Research, Management Science <P>The cross-entropy (CE) method is one of the most significant developments in randomized optimization and simulation in recent years. This book explains in detail how and why the CE method works. The simplicity an
Subject:
Computers Reference-Simulation
Subject:
Operations Research, Management Science
Subject:
Operation Research/Decision Theory
Subject:
Computer Science
Subject:
B
Subject:
Computer simulation
Subject:
Operations Research
Subject:
Engineering
Copyright:
Edition Description:
1st Edition. Softcover version of original hardcover edition 2004
Series:
Information Science and Statistics
Publication Date:
20110701
Binding:
TRADE PAPER
Language:
English
Pages:
321
Dimensions:
235 x 155 mm

Related Subjects

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The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning (Information Science and Statistics) New Trade Paper
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$209.75 In Stock
Product details 321 pages Springer - English 9781441919403 Reviews:
"Synopsis" by , Rubinstein is the pioneer of the well-known score function and cross-entropy methods. Accessible to a broad audience of engineers, computer scientists, mathematicians, statisticians and in general anyone, theorist and practitioner, who is interested in smart simulation, fast optimization, learning algorithms, and image processing.
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