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Discrete Appl Math. 2016 May 11;204:208-212.

Lower Bounds on Paraclique Density.

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Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN, USA, 37996.


The scientific literature teems with clique-centric clustering strategies. In this paper we analyze one such method, the paraclique algorithm. Paraclique has found practical utility in a variety of application domains, and has been successfully employed to reduce the effects of noise. Nevertheless, its formal analysis and worst-case guarantees have remained elusive. We address this issue by deriving a series of lower bounds on paraclique densities.


clique; clustering; graph density; paraclique

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