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Book Categories |
| Preface | ||
| Output analysis for approximated stochastic programs | 1 | |
| Combinatorial Randomized Rounding: Boosting Randomized Rounding with Combinatorial Arguments | 31 | |
| Statutory Regulation of Casualty Insurance Companies: An Example from Norway with Stochastic Programming Analysis | 55 | |
| Option pricing in a world with arbitrage | 87 | |
| Monte Carlo Methods for Discrete Stochastic Optimization | 97 | |
| Discrete Approximation in Quantile Problem of Portfolio Selection | 121 | |
| Optimizing electricity distribution using two-stage integer recourse models | 137 | |
| A Finite-Dimensional Approach to Infinite-Dimensional Constraints in Stochastic Programming Duality | 155 | |
| Non-Linear Risk of Linear-Instruments | 169 | |
| Multialgorithms for Parallel Computing: A New Paradigm for Optimization | 183 | |
| Convergence Rate of Incremental Subgradient Algorithms | 223 | |
| Transient Stochastic Models for Search Patterns | 265 | |
| Value-at-Risk Based Portfolio Optimization | 279 | |
| Combinatorial Optimization, Cross-Entropy, Ants and Rare Events | 303 | |
| Consistency of Statistical Estimators: the Epigraphical View | 365 | |
| Hierarchical Sparsity in Multistage Convex Stochastic Programs | 385 | |
| Conditional Value-at-Risk: Optimization Approach | 411 |
| Price | Condition | Delivery | Seller | Action |
| $278.00 | Digital |
| WonderClub |
Antoine Britt
reviewed Stochastic Optimization (Applied Optimization Series): Algorithms and Applications, Vol. 54 on June 27, 2020
Stochastic Optimization (Applied Optimization Series)
If you read this book as first time in order to understand Computational Complexity, then you're probably not going to like it. You need to read Sipser's textbook before you read this book and make sure that you have a strong background in discrete mathematics (if not, then see Rosen's textbook in Discrete Mathematics). This book is recommended by best people in complexity and algorithms such as Scott Aaronson, Sipser, etc. You need to solve as many exercises as you go.
The book has five parts:
Part I: Algorithms
Part II: Logic
Part III: P and NP
Part IV: Inside P
Part V: Beyond NP
The most important parts are in Part I, III.
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