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003 | OCoLC | ||
005 | 20171106121152.0 | ||
006 | m o d | ||
007 | cr ||||||||||| | ||
008 | 130509s2013 nju ob 001 0 eng | ||
010 | _a 2013019187 | ||
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050 | 0 | 0 | _aT57.64 |
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_aMAT _x041000 _2bisacsh |
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_a518/.282 _223 |
100 | 1 | _aRubinstein, Reuven Y. | |
245 | 1 | 0 |
_aFast sequential Monte Carlo methods for counting and optimization / _cReuven Rubinstein, Faculty of Industrial Engineering and Management, Technion, Israel Institute of Technology, Haifa, Israel, Ad Ridder, Department of Econometrics and Operations Research, Vrije University, Amsterdam, Netherlands, Radislav Vaisman, Faculty of Industrial Engineering and Management, Technion, Israel Institute of Technology, Haifa, Israel. _h[electronic resource] |
264 | 1 |
_aHoboken, New Jersey : _bJohn Wiley & Sons, Inc., _c[2013] |
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300 | _a1 online resource. | ||
336 |
_atext _2rdacontent |
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337 |
_acomputer _2rdamedia |
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338 |
_aonline resource _2rdacarrier |
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490 | 1 | _aWiley series in probability and statistics | |
504 | _aIncludes bibliographical references and index. | ||
505 | 0 | _aSeries; Copyright; Dedication; Chapter 1: Introduction to Monte Carlo Methods; Chapter 2: Cross-Entropy Method; 2.1 Introduction; 2.2 Estimation of Rare-Event Probabilities; 2.3 Cross-Entropy Method forOptimization; 2.4 Continuous Optimization; 2.5 Noisy Optimization; Chapter 3: Minimum Cross-Entropy Method; 3.1 Introduction; 3.2 Classic MinxEnt Method; 3.3 Rare Events and MinxEnt; 3.4 Indicator MinxEnt Method; 3.5 IME Method for Combinatorial Optimization; Chapter 4: Splitting Method for Counting and Optimization; 4.1 Background; 4.2 Quick Glance at the Splitting Method | |
505 | 8 | _a4.3 Splitting Algorithm with Fixed Levels4.4 Adaptive Splitting Algorithm; 4.5 Sampling Uniformly on Discrete Regions; 4.6 Splitting Algorithm for Combinatorial Optimization; 4.7 Enhanced Splitting Method for Counting; 4.8 Application of Splitting to Reliability Models; 4.9 Numerical Results with the Splitting Algorithms; 4.10 Appendix: Gibbs Sampler; Chapter 5: Stochastic Enumeration Method; 5.1 Introduction; 5.2 OSLA Method and Its Extensions; 5.3 SE Method; 5.4 Applications of SE; 5.5 Numerical Results; Appendix A: Additional Topics; A.1 Combinatorial Problems; A.2 Information | |
505 | 8 | _aA.3 Efficiency of EstimatorsBibliography; Abbreviations and Acronyms; List of Symbols; Index; Series | |
520 | _aThis book presents the first comprehensive account of fast sequential Monte Carlo (SMC) methods for counting and optimization at an exceptionally accessible level. Written by authorities in the field, it places great emphasis on cross-entropy, minimum cross-entropy, splitting, and stochastic enumeration. The overall aim is to make SMC methods accessible to readers who want to apply and to accentuate the unifying and novel mathematical ideas behind SMC in their future studies or work. | ||
588 | _aDescription based on print version record and CIP data provided by publisher. | ||
650 | 0 | _aMonte Carlo method. | |
650 | 0 | _aMathematical optimization. | |
650 | 7 |
_aMATHEMATICS _xNumerical Analysis. _2bisacsh |
|
650 | 7 |
_aMathematical optimization. _2fast _0(OCoLC)fst01012099 |
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650 | 7 |
_aMonte Carlo method. _2fast _0(OCoLC)fst01025819 |
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650 | 7 |
_aSequentielle Monte-Carlo-Methode. _2gnd |
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650 | 7 |
_aOptimierung. _2gnd |
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655 | 4 | _aElectronic books. | |
700 | 1 |
_aRidder, Ad, _d1955- |
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700 | 1 | _aVaisman, Radislav. | |
776 | 0 | 8 |
_iPrint version: _aRubinstein, Reuven Y. _tFast sequential Monte Carlo methods for counting and optimization _dHoboken, New Jersey : John Wiley & Sons, Inc., [2013] _z9781118612262 _w(DLC) 2013011113 |
830 | 0 | _aWiley series in probability and statistics. | |
856 | 4 | 0 |
_uhttp://onlinelibrary.wiley.com/book/10.1002/9781118612323 _zWiley Online Library |
942 |
_2ddc _cBK |
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999 |
_c206721 _d206721 |