Pseudometric-Weighted Correlation Clustering via Spectral Preclustering
We study pseudometric-weighted correlation clustering, where every pair of vertices carries a nonnegative disagreement weight and the weights satisfy the triangle inequality. For every fixed $\varepsilon>0$, we give a randomized polynomial-time $(2+\varepsilon)$-approximation, improving the previously best known factor...