English

Polynomial Time Algorithm for $2$-Stable Clustering Instances

Data Structures and Algorithms 2017-02-14 v2

Abstract

Clustering with most objective functions is NP-Hard, even to approximate well in the worst case. Recently, there has been work on exploring different notions of stability which lend structure to the problem. The notion of stability, α\alpha-perturbation resilience, that we study in this paper was originally introduced by Bilu et al.~\cite{Bilu10}. The works of Awasthi et al~\cite{Awasthi12} and Balcan et al.~\cite{Balcan12} provide a polynomial time algorithm for 33-stable and (1+2)(1+\sqrt{2})-stable instances respectively. This paper provides a polynomial time algorithm for 22-stable instances, improving on and answering an open question in ~\cite{Balcan12}.

Keywords

Cite

@article{arxiv.1607.07431,
  title  = {Polynomial Time Algorithm for $2$-Stable Clustering Instances},
  author = {Ainesh Bakshi and Nadiia Chepurko},
  journal= {arXiv preprint arXiv:1607.07431},
  year   = {2017}
}

Comments

Bug in Lemma 3.2

R2 v1 2026-06-22T15:03:52.485Z