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Viser: Computational Complexity of Counting and Sampling
Computational Complexity of Counting and Sampling Vital Source e-bog
Istvan Miklos
(2019)
Computational Complexity of Counting and Sampling
Istvan Miklos
(2019)
Sprog: Engelsk
Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: Taylor & Francis (Februar 2019)
- ISBN: 9781351971607
Bookshelf online: 5 år fra købsdato.
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Detaljer om varen
- Paperback: 390 sider
- Udgiver: CRC Press LLC (Februar 2019)
- ISBN: 9781138035577
Computational Complexity of Counting and Samplingprovides readers with comprehensive and detailed coverage of the subject of computational complexity. It is primarily geared for researchers in enumerative combinatorics, discrete mathematics and theoretical computer science.
The book covers three topics: Counting problems that are solvable in polynomial running time; Approximation of algorithms for counting and sampling; Holographic algorithms.
First, it opens with the basics such as the algorithmic point of view, dynamic programming algorithms and theoretical computer science point of view. Later, the book expands its scope to focus on advanced topics like stochastic approximations of counting computational objects and holographic algorithms. After finishing the book, readers will agree that the subject is well covered as the book starts with the basics and gradually explores the more complex aspects of the topic.
Features:
- Each chapter includes exercises and solutions
- Ideally written for researchers and scientists
- Covers all aspects of the topic beginning with a solid introduction before shifting to computational complexity's more advanced features with a focus on counting and sampling
Features:
- Each chapter includes exercises and solutions
- Ideally written for researchers and scientists
- Covers all aspects of the topic beginning with a solid introduction before shifting to computational complexity's more advanced features with a focus on counting and sampling
1. Background on computational complexity
2. Algebraic dynamic programming and monotone computations
3. Linear algebraic algorithms. The power of subtracting
4. #P-complete counting problems
5. Holographic algorithms
6. Methods of random generations
7. Mixing of Markov chains and their applications in the theory of counting and sampling
8. Approximable counting and sampling problems