Pruned Pivot Algorithm For Correlation - Latest Information & Updates 2026

Web Reference: Inspired by the prevalence of large graphs and constantly changing data in modern applications, we study correlation clustering in dynamic, parallel (MPC), and local computation (LCA) settings. We design an approach that im-proves state-of-the-art runtime complexities in all these settings. Feb 24, 2024 · Inspired by the prevalence of large graphs and constantly changing data in modern applications, we study correlation clustering in dynamic, parallel (MPC), and local computation (LCA) settings. In particular, we provide the first fully dynamic algorithm that runs in an expected amortized constant time, without any dependence on the graph size. Moreover, our algorithm essentially matches the approximation guarantee of the celebrated PIVOT algorithm.

YouTube Excerpt: Konstantin Makarychev (Northwestern University):

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Near Optimal LP Rounding for Correlation Clustering on Complete Graphs

[NeurIPS 2019] Correlation Clustering with Local Objectives

Breaking 3-Factor Approximation for Correlation Clustering in Polylogarithmic Rounds

Data Science || Machine Learning || Correlation v/s Covariance

Recent Progress on Correlation Clustering - Vincent Cohen-Addad

SIMON How To: SAM correlation clustering

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IDEAL Workshop: Weiyun Ma, Almost 3-Approximate Correlation Clustering in Constant Rounds

Correlated Rounding for Correlation Clustering by Alantha Newman

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Last Updated: April 3, 2026

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