The Cross-Entropy Method by Reuven Y Rubinstein
Our aim was to write a book on the CE method which was accessible to advanced undergraduate students and engineers who simply want to apply the CE method in their work, while at the same time accentu ating the unifying and novel mathematical ideas behind the CE method, so as to stimulate further research at a postgraduate level.-
Pattern Recognition and Machine Learning
-
Bayesian Networks and Decision Graphs
-
Novelty, Information and Surprise
-
Computational Methods in Biometric Authentication
-
Statistical Image Processing and Multidimensional Modeling
-
The Practice of Time Series Analysis
-
Computer Intrusion Detection and Network Monitoring
-
Probabilistic Networks and Expert Systems
-
Information Theoretic Learning
-
Estimation of Dependences Based on Empirical Data
-
Probabilistic Conditional Independence Structures
-
Information and Complexity in Statistical Modeling
-
Feedforward Neural Network Methodology
-
Statistical and Inductive Inference by Minimum Message Length
-
Cumulative Sum Charts and Charting for Quality Improvement
-
Nonlinear Dimensionality Reduction
-
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
-
Support Vector Machines
-
The Nature of Statistical Learning Theory
-
Sequential Monte Carlo Methods in Practice
From the reviews:
"Rarely have I seen such a dense and straight to the point pedagogical monograph on such a modern subjectThis 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
"...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
"This book describes the cross-entropy method for a range of optimization problems. … It is a substantial contribution to stochastic optimization and more generally to the stochastic numerical methods theory." (V.V.Fedorov, Short Book Reviews, Vol. 25 (1), 2005)
"Since the CE method is a young and developing field, there is no book available in this area where the two authors are the pioneers. Therefore, it is quite a unique book and it may become a classic reference in the CE method literature." Technometrics, February 2005
"This book is a comprehensive introduction to the cross-entropy method which was invented in 1997 by the first author … . The book is … written for advanced undergraduate students and engineers who want to apply the method. The authors made an effort to avoid formal mathematical ‘definition-lemma-theorem-proof’ style, aiming to promote the ideas and not burden the reader with too much technical detail. My impression is that they were quite successful." (J. Zerovnik, Journal of the Operational Research Society, Vol. 57 (12), 2006)
"This book is a comprehensive review of the cross-entropy (CE) method and its various applications, in particular for rare-event simulation and combinatorial optimisation. … Each chapter is copiously illustrated by numerical examples. … we highly recommend this book to anybody curiousabout simulation methods, or more generally about applied probability. The principle behind the CE method is remarkably simple and intellectually appealing, and the authors do a very good job of explaining how it works, and why it works well." (Nicolas Chopin, Journal of Applied Statistics, Vol. 33 (8), 2006)
"The authors have produced a routine … that identifies cases where CE codes not perform well, and thus alerts one when other methods may be more appropriate. Having FACE available to test CE performance enhances the attractiveness of both CE and this book. … In summary, this book is a good introduction to CE for those who want to use the method, in particular, for optimization situations." (David E. Booth, Technometrics, Vol. 50 (1), 2008)
"This book is a good introduction to the cross-entropy (CE) method, an approach to combinatorial optimization and rare-event simulation based on minimizing the cross-entropy … between a sampling distribution and an unknown target distribution. It is intended to be ‘accessible to advanced undergraduate students and engineers who simply want to apply the CE method in their work, while at the same time accentuating the unifying and novel ideas behind the CE method.’" (David Bulger, Zentralblatt MATH, Vol. 1140, 2008)
Thomas Taimre, PhD, is a Postdoctoral Research Fellow at The University of Queensland. He currently focuses his research on Monte Carlo methods and simulation, from the theoretical foundations to performing computer implementations.
Zdravko I. Botev, PhD, is a Postdoctoral Research Fellow at the University of Montreal (Canada). His research interests include the splitting method for rare-event simulation and kernel density estimation. He is the author of one of the most widely used free MATLAB(R) statistical software programs for nonparametric kernel density estimation.
| SKU | Unavailable |
| ISBN 13 | 9780387212401 |
| ISBN 10 | 038721240X |
| Title | The Cross-Entropy Method |
| Author | Reuven Y Rubinstein |
| Series | Information Science And Statistics |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer-Verlag New York Inc. |
| Year published | 2004-07-28 |
| Number of pages | 301 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |