Beyond the Worst-Case Analysis of Algorithms
«'Many important algorithmic problems are considered intractable according to the conventional worst-case metrics of computational complexity theory. This important book demonstrates that, for many such problems, it is possible to craft algorithms that perform well under plausible assumptions about the structure of the inputs that are likely to be presented. It may well mark a turning point in the field of algorithm design and analysis.' Richard M. Karp, University of California at Berkeley»
There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. Les mer
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Detaljer
- Forlag
- Cambridge University Press
- Innbinding
- Innbundet
- Språk
- Engelsk
- ISBN
- 9781108494311
- Utgivelsesår
- 2021
- Format
- 26 x 19 cm
Anmeldelser
«'Many important algorithmic problems are considered intractable according to the conventional worst-case metrics of computational complexity theory. This important book demonstrates that, for many such problems, it is possible to craft algorithms that perform well under plausible assumptions about the structure of the inputs that are likely to be presented. It may well mark a turning point in the field of algorithm design and analysis.' Richard M. Karp, University of California at Berkeley»
«'The worst-case analysis sets a criteria for perfect algorithmic performance. It has led and will continue to lead to the creation of breakthrough algorithms unthinkable by previous generations. But the success of worst-case analysis as the main theoretical computing framework has also placed provably-good algorithm design in a quandary, because nearly all practically significant problems have been shown to be intractable under such perfect criteria. Going beyond the worst-case analysis is a much-needed step for the theory of computing. This book - broad in scope and united by a common theme - represents diverse efforts in the field, and will elevate this fundamental subject for connecting computing theory with the rapid advances in Big Data and AI Solutions.' Shanghua Teng, University of Southern California»
«'The book is a must have for any aspiring algorithm researcher … Essential.' D. Papamichail, Choice Magazine»