£59.17

Cambridge University Press Kernelization: Theory of Parameterized Preprocessing

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£61.00 £55.61 £56.79 £57.96 £59.14 £60.31 £61.49 10 May 2026 27 May 2026 13 June 2026 30 June 2026 17 July 2026

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Description

Preprocessing, or data reduction, is a standard technique for simplifying and speeding up computation. Written by a team of experts in the field, this book introduces a rapidly developing area of preprocessing analysis known as kernelization. The authors provide an overview of basic methods and important results, with accessible explanations of the most recent advances in the area, such as meta-kernelization, representative sets, polynomial lower bounds, and lossy kernelization. The text is divided into four parts, which cover the different theoretical aspects of the area: upper bounds, meta-theorems, lower bounds, and beyond kernelization. The methods are demonstrated through extensive examples using a single data set. Written to be self-contained, the book only requires a basic background in algorithmics and will be of use to professionals, researchers and graduate students in theoretical computer science, optimization, combinatorics, and related fields.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
10 January 2019
Listed Since
23 June 2018

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