商品簡介
Computational Complexity of Counting and Sampling provides 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
作者簡介
Istvan Miklos is a Hungarian mathematician and bioinformatician at the Renyi Institute in Budapest. He holds a Ph.D. from Eotvos University in Budapest. His research interests lie in theoretical and applied computer science and combinatorics, particularly in the study of Markov chain, Monte Carlo methods and in sampling and counting combinatorial objects appearing in applied mathematics. He has more than 50 peer-reviewed scientific papers.
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