Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6871952 | Discrete Applied Mathematics | 2016 | 5 Pages |
Abstract
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.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Ronald D. Hagan, Michael A. Langston, Kai Wang,