AISTATS 2021poster15 citations
Consistent k-Median: Simpler, Better and Robust
Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian
Abstract
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 [18]. 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 [18].
BibTeX
@InProceedings{pmlr-v130-guo21a,
title = { Consistent k-Median: Simpler, Better and Robust },
author = {Guo, Xiangyu and Kulkarni, Janardhan and Li, Shi and Xian, Jiayi},
booktitle = {Proceedings of The 24th International Conference on Artificial Intelligence and Statistics},
pages = {1135--1143},
year = {2021},
editor = {Banerjee, Arindam and Fukumizu, Kenji},
volume = {130},
series = {Proceedings of Machine Learning Research},
month = {13--15 Apr},
publisher = {PMLR},
pdf = {http://proceedings.mlr.press/v130/guo21a/guo21a.pdf},
url = {https://proceedings.mlr.press/v130/guo21a.html},
abstract = { 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 [18]. 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 [18]. }
}