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

Konstantin Makarychev, Sayak Chakrabarty

Keywords: correlation clustering, Pivot algorithm, streaming

TL;DR: We show that a variant of the Pivot algorithm for Correlation Clustering gives a (3+eps) approximation in the single-pass semi-streaming model with O(n/eps) words of memory.

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.

Submission Number: 14957