Parameterized Algorithms

Fedor V. Fomin; Daniel Lokshtanov; Saket Saurabh; Meirav Zehavi

doi:10.1017/9781108637435.004

Parameterized Algorithms

Fedor V. Fomin
, Daniel Lokshtanov
, Saket Saurabh
, Meirav Zehavi

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Scopus citations

Abstract

Parameterized algorithmics analyzes running time in finer detail than classical complexity theory: instead of expressing the running time of an algorithm as a function of the input size only, dependence on one or more parameters of the input instance is taken into account. In this chapter we sketch some techniques and tools from this rapidly developing area.

Original language	English
Title of host publication	Beyond the Worst-Case Analysis of Algorithms
Publisher	Cambridge University Press
Pages	27-51
Number of pages	25
ISBN (Electronic)	9781108637435
ISBN (Print)	9781108494311
DOIs	https://doi.org/10.1017/9781108637435.004
State	Published - 1 Jan 2021

ASJC Scopus subject areas

General Computer Science
General Mathematics

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10.1017/9781108637435.004

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abstract = "Parameterized algorithmics analyzes running time in finer detail than classical complexity theory: instead of expressing the running time of an algorithm as a function of the input size only, dependence on one or more parameters of the input instance is taken into account. In this chapter we sketch some techniques and tools from this rapidly developing area.",

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AU - Lokshtanov, Daniel

AU - Saurabh, Saket

AU - Zehavi, Meirav

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N2 - Parameterized algorithmics analyzes running time in finer detail than classical complexity theory: instead of expressing the running time of an algorithm as a function of the input size only, dependence on one or more parameters of the input instance is taken into account. In this chapter we sketch some techniques and tools from this rapidly developing area.

AB - Parameterized algorithmics analyzes running time in finer detail than classical complexity theory: instead of expressing the running time of an algorithm as a function of the input size only, dependence on one or more parameters of the input instance is taken into account. In this chapter we sketch some techniques and tools from this rapidly developing area.

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M3 - Chapter

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SN - 9781108494311

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BT - Beyond the Worst-Case Analysis of Algorithms

PB - Cambridge University Press

ER -

Parameterized Algorithms

Abstract

ASJC Scopus subject areas

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