Consistent k-Median: Simpler, Better and Robust
Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:1135-1143, 2021.
In this paper we introduce and study the online consistent k-clustering with outliers problem, generalizing the non-outlier version of the problem studied in Lattanzi-Vassilvitskii . We show that a simple local-search based on-line algorithm can give a bicriteria constant approximation for the problem with O(k^2 log^2(nD)) swaps of medians (recourse) in total, where D is the diameter of the metric. When restricted to the problem without outliers, our algorithm is simpler, deterministic and gives better approximation ratio and recourse, compared to that of Lattanzi-Vassilvitskii .