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Part of book or chapter of book . 1999 . Peer-reviewed
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Probabilistic analysis of approximation algorithms

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Other literature type 01 Jan 1999 English Publisher:Springer Berlin Heidelberg
Authors: Alberto Marchetti-Spaccamela; Giorgio Ausiello; Giorgio Gambosi; Marco Protasi; Pierluigi Crescenzi; Viggo Kann;

doi: 10.1007/978-3-642-58412-1_9

Probabilistic analysis of approximation algorithms

Abstract

IN PREVIOUS chapters the performance of an approximate algorithm has been analyzed using a worst case point of view. In this chapter this condition is relaxed and the probabilistic analysis of an algorithm is performed by considering either the average case or the behavior in almost all cases.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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