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Fast sequential Monte Carlo methods for counting and optimization / / Reuven Rubinstein, Ad Ridder, Radislav Vaisman
| Fast sequential Monte Carlo methods for counting and optimization / / Reuven Rubinstein, Ad Ridder, Radislav Vaisman |
| Autore | Rubinstein Reuven Y |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2014] |
| Descrizione fisica | 1 online resource (208 p.) |
| Disciplina | 518/.282 |
| Altri autori (Persone) |
RidderAd <1955->
VaismanRadislav |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Mathematical optimization
Monte Carlo method |
| ISBN |
1-118-61235-3
1-118-61232-9 1-118-61231-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page; Contents; Preface; 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-Entrophy Method for Optimization; 2.3.1. The Multidimensional 0/1 Knapsack Problem; 2.3.2. Mastermind Game; 2.3.3. Markov Decision Process and Reinforcement Learning; 2.4. Continuous Optimization; 2.5. Noisy Optimization; 2.5.1. Stopping Criterion; 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
3.4.1. Connection between CE and IME3.5. IME Method for Combinatorial Optimization; 3.5.1. Unconstrained Combinatorial Optimization; 3.5.2. Constrained Combinatorial Optimization: The Penalty Function Approach; Chapter 4 Splitting Method for Counting and Optimization; 4.1. Background; 4.2. Quick Glance at the Splitting Method; 4.3. Splitting Algorithm with Fixed Levels; 4.4. Adaptive Splitting Algorithm; 4.5. Sampling Uniformly on Discrete Regions; 4.6. Splitting Algorithm for Combinatorial Optimization; 4.7. Enhanced Splitting Method for Counting; 4.7.1. Counting with the Direct Estimator 4.7.2. Counting with the Capture-Recapture Method4.8. Application of Splitting to Reliability Models; 4.8.1. Introduction; 4.8.2. Static Graph Reliability Problem; 4.8.3. BMC Algorithm for Computing S(Y); 4.8.4. Gibbs Sampler; 4.9. Numerical Results with the Splitting Algorithms; 4.9.1. Counting; 4.9.2. Combinatorial Optimization; 4.9.3. Reliability Models; 4.10. Appendix: Gibbs Sampler; Chapter 5 Stochastic Enumeration Method; 5.1. Introduction; 5.2. OSLA Method and Its Extensions; 5.2.1. Extension of OSLA: nSLA Method; 5.2.2. Extension of OSLA for SAW: Multiple Trajectories; 5.3. SE Method 5.3.1. SE Algorithm5.4. Applications of SE; 5.4.1. Counting the Number of Trajectories in a Network; 5.4.2. SE for Probabilities Estimation; 5.4.3. Counting the Number of Perfect Matchings in a Graph; 5.4.4. Counting SAT; 5.5. Numerical Results; 5.5.1. Counting SAW; 5.5.2. Counting the Number of Trajectories in a Network; 5.5.3. Counting the Number of Perfect Matchings in a Graph; 5.5.4. Counting SAT; 5.5.5. Comparison of SE with Splitting and SampleSearch; Appendix A Additional Topics; A.1. Combinatorial Problems; A.1.1. Counting; A.1.2. Combinatorial Optimization; A.2. Information A.2.1. Shannon EntropyA.2.2. Kullback-Leibler Cross-Entropy; A.3. Efficiency of Estimators; A.3.1. Complexity; A.3.2. Complexity of Randomized Algorithms; Bibliography; Abbreviations and Acronyms; List of Symbols; Index; Series Page |
| Record Nr. | UNINA-9910139030003321 |
Rubinstein Reuven Y
|
||
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fast sequential Monte Carlo methods for counting and optimization / / Reuven Rubinstein, Ad Ridder, Radislav Vaisman
| Fast sequential Monte Carlo methods for counting and optimization / / Reuven Rubinstein, Ad Ridder, Radislav Vaisman |
| Autore | Rubinstein Reuven Y |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2014] |
| Descrizione fisica | 1 online resource (208 p.) |
| Disciplina | 518/.282 |
| Altri autori (Persone) |
RidderAd <1955->
VaismanRadislav |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Mathematical optimization
Monte Carlo method |
| ISBN |
1-118-61235-3
1-118-61232-9 1-118-61231-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page; Contents; Preface; 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-Entrophy Method for Optimization; 2.3.1. The Multidimensional 0/1 Knapsack Problem; 2.3.2. Mastermind Game; 2.3.3. Markov Decision Process and Reinforcement Learning; 2.4. Continuous Optimization; 2.5. Noisy Optimization; 2.5.1. Stopping Criterion; 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
3.4.1. Connection between CE and IME3.5. IME Method for Combinatorial Optimization; 3.5.1. Unconstrained Combinatorial Optimization; 3.5.2. Constrained Combinatorial Optimization: The Penalty Function Approach; Chapter 4 Splitting Method for Counting and Optimization; 4.1. Background; 4.2. Quick Glance at the Splitting Method; 4.3. Splitting Algorithm with Fixed Levels; 4.4. Adaptive Splitting Algorithm; 4.5. Sampling Uniformly on Discrete Regions; 4.6. Splitting Algorithm for Combinatorial Optimization; 4.7. Enhanced Splitting Method for Counting; 4.7.1. Counting with the Direct Estimator 4.7.2. Counting with the Capture-Recapture Method4.8. Application of Splitting to Reliability Models; 4.8.1. Introduction; 4.8.2. Static Graph Reliability Problem; 4.8.3. BMC Algorithm for Computing S(Y); 4.8.4. Gibbs Sampler; 4.9. Numerical Results with the Splitting Algorithms; 4.9.1. Counting; 4.9.2. Combinatorial Optimization; 4.9.3. Reliability Models; 4.10. Appendix: Gibbs Sampler; Chapter 5 Stochastic Enumeration Method; 5.1. Introduction; 5.2. OSLA Method and Its Extensions; 5.2.1. Extension of OSLA: nSLA Method; 5.2.2. Extension of OSLA for SAW: Multiple Trajectories; 5.3. SE Method 5.3.1. SE Algorithm5.4. Applications of SE; 5.4.1. Counting the Number of Trajectories in a Network; 5.4.2. SE for Probabilities Estimation; 5.4.3. Counting the Number of Perfect Matchings in a Graph; 5.4.4. Counting SAT; 5.5. Numerical Results; 5.5.1. Counting SAW; 5.5.2. Counting the Number of Trajectories in a Network; 5.5.3. Counting the Number of Perfect Matchings in a Graph; 5.5.4. Counting SAT; 5.5.5. Comparison of SE with Splitting and SampleSearch; Appendix A Additional Topics; A.1. Combinatorial Problems; A.1.1. Counting; A.1.2. Combinatorial Optimization; A.2. Information A.2.1. Shannon EntropyA.2.2. Kullback-Leibler Cross-Entropy; A.3. Efficiency of Estimators; A.3.1. Complexity; A.3.2. Complexity of Randomized Algorithms; Bibliography; Abbreviations and Acronyms; List of Symbols; Index; Series Page |
| Record Nr. | UNINA-9910807943703321 |
|
Rubinstein Reuven Y
|
||
| Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||