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Poster

Single-Pass Pivot Algorithm for Correlation Clustering. Keep it simple!

Konstantin Makarychev · Sayak Chakrabarty

Great Hall & Hall B1+B2 (level 1) #1915
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Thu 14 Dec 8:45 a.m. PST — 10:45 a.m. PST

Abstract:

We show that a simple single-pass semi-streaming variant of the Pivot algorithm for Correlation Clustering gives a (3+eps)-approximation using O(n/eps) words of memory. This is a slight improvement over the recent results of Cambus, Kuhn, Lindy, Pai, and Uitto, who gave a (3+eps)-approximation using O(n log n) words of memory, and Behnezhad, Charikar, Ma, and Tan, who gave a 5-approximation using O(n) words of memory. One of the main contributions of our paper is that the algorithm and its analysis are simple and easy to understand.

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