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Consistent $k$-Median: Simpler, Better and Robust

2020-08-13 · Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian

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, ICML17]. We show that a simple local-search based online 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, ICML17].

📄 PDF Abstract BibTeX arXiv:2008.06101

Code (1)

xyguo/OnlineKZMedian 공식 구현

Tasks

Clustering

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