Local Correlation Clustering with Asymmetric Classification Errors

no code implementations • 11 Aug 2021 • Jafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev

In the Correlation Clustering problem, we are given a complete weighted graph $G$ with its edges labeled as "similar" and "dissimilar" by a noisy binary classifier.

Classification Clustering

Correlation Clustering with Asymmetric Classification Errors

no code implementations • ICML 2020 • Jafar Jafarov, Sanchit Kalhan, Konstantin Makarychev, Yury Makarychev

In the Correlation Clustering problem, we are given a weighted graph $G$ with its edges labeled as "similar" or "dissimilar" by a binary classifier.

Classification Clustering

Correlation clustering with local objectives

no code implementations • NeurIPS 2019 • Sanchit Kalhan, Konstantin Makarychev, Timothy Zhou

Classically, we are tasked with producing a clustering that minimizes the number of disagreements: an edge is in disagreement if it is a similar edge and is present across clusters or if it is a dissimilar edge and is present within a cluster.

Clustering graph partitioning