Approximation Algorithm for Min-Max Correlation Clustering Problem with Outliers.

In this paper, we investigate the min-max correlation clustering problem with outliers, which is a combination of the min-max correlation clustering problem with the robust clustering. We first prove that the problem is NP-hard to obtain any finite approximation algorithm. Then we design an approximation algorithm based on LP-rounding technique and receive a bi-criteria guarantee.