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Local Correlation Clustering with Asymmetric Classification Errors
[article]

2021
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arXiv
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pre-print

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. For a clustering 𝒞 of graph G, a similar edge is in disagreement with 𝒞, if its endpoints belong to distinct clusters; and a dissimilar edge is in disagreement with 𝒞 if its endpoints belong to the same cluster. The disagreements vector, dis, is a vector indexed by the vertices of G such that the v-th coordinate dis_v equals the

arXiv:2108.05697v1
fatcat:atq4xysqzrdnnl2rxqokk7vuqm