Randomized algorithms : approximation, generation, and counting /
Randomized Algorithms discusses two problems of fine pedigree: counting and generation, both of which are of fundamental importance to discrete mathematics and probability. When asking questions like "How many are there?" and "What does it look like on average?" of families of co...
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| Format: | eBook |
| Language: | English |
| Published: |
London ; New York :
Springer,
2001.
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| Series: | CPHC/BCS distinguished dissertations.
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| Online Access: | Connect to the full text of this electronic book |
| Summary: | Randomized Algorithms discusses two problems of fine pedigree: counting and generation, both of which are of fundamental importance to discrete mathematics and probability. When asking questions like "How many are there?" and "What does it look like on average?" of families of combinatorial structures, answers are often difficult to find -- we can be blocked by seemingly intractable algorithms. Randomized Algorithms shows how to get around the problem of intractability with the Markov chain Monte Carlo method, as well as highlighting the method's natural limits. It uses the technique of coupling before introducing "path coupling" a new technique which radically simplifies and improves upon previous methods in the area. |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (xvi, 152 pages) : illustrations. |
| Format: | Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |
| Bibliography: | Includes bibliographical references (pages [139]-148) and index. |
| ISBN: | 9781447106951 (electronic bk.) 1447106954 (electronic bk.) |
| ISSN: | 1439-9768 |