Chekuri, Chandra ;
Gupta, Shalmoli
Perturbation Resilient Clustering for k-Center and Related Problems via LP Relaxations
Abstract
We consider clustering in the perturbation resilience model that has been studied since the work of Bilu and Linial [Yonatan Bilu and Nathan Linial, 2010] and Awasthi, Blum and Sheffet [Awasthi et al., 2012]. A clustering instance I is said to be alpha-perturbation resilient if the optimal solution does not change when the pairwise distances are modified by a factor of alpha and the perturbed distances satisfy the metric property - this is the metric perturbation resilience property introduced in [Angelidakis et al., 2017] and a weaker requirement than prior models. We make two high-level contributions.
- We show that the natural LP relaxation of k-center and asymmetric k-center is integral for 2-perturbation resilient instances. We belive that demonstrating the goodness of standard LP relaxations complements existing results [Maria{-}Florina Balcan et al., 2016; Angelidakis et al., 2017] that are based on new algorithms designed for the perturbation model.
- We define a simple new model of perturbation resilience for clustering with outliers. Using this model we show that the unified MST and dynamic programming based algorithm proposed in [Angelidakis et al., 2017] exactly solves the clustering with outliers problem for several common center based objectives (like k-center, k-means, k-median) when the instances is 2-perturbation resilient. We further show that a natural LP relxation is integral for 2-perturbation resilient instances of k-center with outliers.
BibTeX - Entry
@InProceedings{chekuri_et_al:LIPIcs:2018:9413,
author = {Chandra Chekuri and Shalmoli Gupta},
title = {{Perturbation Resilient Clustering for k-Center and Related Problems via LP Relaxations}},
booktitle = {Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2018)},
pages = {9:1--9:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-085-9},
ISSN = {1868-8969},
year = {2018},
volume = {116},
editor = {Eric Blais and Klaus Jansen and Jos{\'e} D. P. Rolim and David Steurer},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2018/9413},
URN = {urn:nbn:de:0030-drops-94136},
doi = {10.4230/LIPIcs.APPROX-RANDOM.2018.9},
annote = {Keywords: Clustering, Perturbation Resilience, LP Integrality, Outliers, Beyond Worst Case Analysis}
}
Keywords: |
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Clustering, Perturbation Resilience, LP Integrality, Outliers, Beyond Worst Case Analysis |
Seminar: |
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Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2018)
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Issue date: |
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2018 |
Date of publication: |
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13.08.2018 |
13.08.2018