Beyond the Worst-Case Analysis of Algorithms (Hardcover)

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. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Release date:	2021
Editors:	Tim Roughgarden
Dimensions:	260 x 188 x 40mm (L x W x T)
Format:	Hardcover
Pages:	704
ISBN-13:	978-1-108-49431-1
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Science & Mathematics > Mathematics > Optimization > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	1-108-49431-5
Barcode:	9781108494311

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