A tutorial on the cross-entropy method

被引:2244
作者
De Boer, PT
Kroese, DP
Mannor, S
Rubinstein, RY
机构
[1] Univ Twente, Dept Elect Engn Math & Comp Sci, NL-7500 AE Enschede, Netherlands
[2] Univ Queensland, Dept Math, Brisbane, Qld 4072, Australia
[3] McGill Univ, Dept Elect & Comp Engn, Montreal, PQ, Canada
[4] Technion Israel Inst Technol, Dept Ind Engn, IL-32000 Haifa, Israel
基金
以色列科学基金会;
关键词
cross-entropy method; Monte-Carlo simulation; randomized optimization; machine learning; rare events;
D O I
10.1007/s10479-005-5724-z
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页码:19 / 67
页数:49
相关论文
共 50 条
[41]  
Rubinstein R. Y., 2004, CROSS ENTROPY METHOD, DOI 10.1007/978-1-4757-4321-0
[42]   Optimization of computer simulation models with rare events [J].
Rubinstein, RY .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1997, 99 (01) :89-112
[43]  
Rubinstein RY, 2001, APPL OPTIMIZAT, V54, P303
[44]  
Rubinstein RY., 1998, Modern simulation and modeling
[45]  
Rubinstein RY, 1993, Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization by the Score Function Method, V13
[46]   Nested partitions method for global optimization [J].
Shi, LY ;
Olafsson, S .
OPERATIONS RESEARCH, 2000, 48 (03) :390-407
[47]  
Sutton RS, 2000, ADV NEUR IN, V12, P1057
[48]  
VOUDOURIS C, 2003, BT TECHNOL J, V16, P46
[49]  
WATKINS CJCH, 1992, MACH LEARN, V8, P279, DOI 10.1007/BF00992698
[50]  
Webb A.R., 1999, STAT PATTERN RECOGNI