Computational Complexity of Counting and Sampling

Computational Complexity of Counting and Sampling provides comprehensive coverage of the subject, covering polynomial running time, #P-complete counting problems, and approximation algorithms. It starts with the basics and gradually explores the more complex aspects of the topic, with exercises and solutions included. It is ideal for researchers and scientists in enumerative combinatorics, discrete mathematics, and theoretical computer science.

Format: Paperback / softback
Length: 390 pages
Publication date: 20 February 2019
Publisher: Taylor & Francis Ltd

Computational Complexity of Counting and Sampling is a comprehensive and detailed book that provides readers with a comprehensive understanding of the subject of computational complexity. It is primarily geared toward researchers in enumerative combinatorics, discrete mathematics, and theoretical computer science. The book covers a wide range of topics, including counting and sampling problems that are solvable in polynomial running time, #P-complete counting problems, and approximation algorithms for counting and sampling.

The book begins with the basics, including the theoretical computer science background and dynamic programming algorithms. It then expands its scope to focus on advanced topics, such as stochastic approximations of counting discrete mathematical 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 of the book include exercises and solutions, which are ideal for researchers and scientists. The book 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.

One of the key features of the book is its emphasis on the practical applications of computational complexity. The authors provide numerous examples of how computational complexity can be used to solve real-world problems, such as counting the number of molecules in a sample, estimating the probability of a disease, and designing efficient algorithms for solving complex problems.

Another important feature of the book is its emphasis on the theoretical foundations of computational complexity. The authors provide a thorough explanation of the various algorithms and techniques used to solve computational complexity problems, and they discuss the theoretical implications of these algorithms.

The book is well-written and accessible to readers with a background in mathematics or computer science. The authors use clear and concise language, and they provide numerous examples to illustrate their points.

In conclusion, Computational Complexity of Counting and Sampling is a valuable resource for researchers and scientists in the field of computational complexity. It provides a comprehensive and detailed coverage of the subject, and it is ideal for researchers and scientists who are interested in learning more about the practical applications of computational complexity and the theoretical foundations of the field.

Weight: 600g
Dimension: 158 x 233 x 23 (mm)
ISBN-13: 9781138035577