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Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)

Single-Pass Streaming Algorithms for Correlation Clustering

Abstract

We study correlation clustering in the streaming setting. This problem has been studied extensively and numerous algorithms have been developed, most requiring multiple passes over the stream. For the important case of single-pass algorithms, recent work of Assadi and Wang [8] obtains a c-approximation using Õ(n) space where c > 105 is a constant and n is the number of vertices to be clustered.
We present a single-pass algorithm that obtains a 5-approximation using O(n) space. The algorithm itself is extremely simple and has implications beyond the streaming setting (such as for dynamic and local computation algorithms). The approximation analysis, on the other hand, is delicate and in fact tight.

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cover image Proceedings
Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)
Pages: 819 - 849
Editors: Nikhil Bansal, University of Michigan, Ann Arbor, Michigan, USA and Viswanath Nagarajan, University of Michigan, Ann Arbor, Michigan, USA
ISBN (Online): 978-1-61197-755-4

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Published online: 16 January 2023

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