Approximate Dual Separation for the Cluster LP: a 1.387 approximation for Correlation Clustering
We give a deterministic $(1.3865+\epsilon)$-approximation for correlation clustering on complete graphs, improving the previous best factor of $1.485+\epsilon$ of Cao et al. (STOC'24). Our first main contribution is an efficient weak separation oracle for the cluster-LP dual. Given signed vertex weights $q$, it either...