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- W1481999670 abstract "Bipartite Correlation clustering is the problem of generating a set of disjoint bi-cliques on a set of nodes while minimizing the symmetric dierence to a bipartite input graph. The number programs which become prohibitive even for modestly sized tasks. In this paper we present an improved factor 4 ap- proximation algorithm to this problem using a simple combinatorial algorithm which does not require solving large convex programs. The analysis extends a method developed by Ailon, Charikar and Alantha in 2008, where a randomized pivoting algorithm was analyzed for obtaining a 3-approximation algorithm for Correlation Clustering, which is the same problem on graphs (not bipartite). The analysis for Correlation Clustering there required dening events for structures containing 3 vertices and" @default.
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- W1481999670 date "2010-12-14" @default.
- W1481999670 modified "2023-09-27" @default.
- W1481999670 title "An Improved Algorithm for Bipartite Correlation Clustering" @default.
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