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Theoretical Computer Science
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Approximating Max NAE-k-SAT by anonymous local search

Approximating Max NAE-\(k\)-SAT by anonymous local search
descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2017 English Publisher:Elsevier BVJournal:Theoretical Computer Science, volume 657, pages 54-63 (issn: 0304-3975, Copyright policy )
Authors: Aiyong Xian; Kaiyuan Zhu; Daming Zhu; Lianrong Pu; Hong Liu 0001;

doi: 10.1016/j.tcs.2016.05.040

Approximating Max NAE-k-SAT by anonymous local search

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Keywords

algorithm, performance ratio, satisfiability, Analysis of algorithms and problem complexity, local search, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), complexity, Approximation algorithms

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selected citations
These citations are derived from selected sources.
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!
1
Average
Average
Average
hybrid
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