Local algorithms for interactive clustering

Pranjal Awasthi, Maria Fiorina Balcan, Konstantin Voevodski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

We study the design of interactive clustering algorithms for data sets satisfying natural stability assumptions. Our algorithms start with any initial clustering and only make local changes in each step; both are desirable features in many applications. We show that in this constrained setting one can still design provably efficient algorithms that produce accurate clusterings. We also show that our algorithms perform well on real-world data.

Original languageAmerican English
Title of host publication31st International Conference on Machine Learning, ICML 2014
PublisherInternational Machine Learning Society (IMLS)
Pages1946-1954
Number of pages9
ISBN (Electronic)9781634393973
StatePublished - 2014
Externally publishedYes
Event31st International Conference on Machine Learning, ICML 2014 - Beijing, China
Duration: Jun 21 2014Jun 26 2014

Publication series

Name31st International Conference on Machine Learning, ICML 2014
Volume3

Other

Other31st International Conference on Machine Learning, ICML 2014
Country/TerritoryChina
CityBeijing
Period6/21/146/26/14

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

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