Multilevel manifold learning with application to spectral clustering

Haw Ren Fang, Sophia Sakellaridi, Yousef Saad

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

7 Scopus citations

Abstract

In the past decade, a number of nonlinear dimensionality reduction methods using an affinity graph have been developed for manifold learning. This paper explores a multilevel framework with the goal of reducing the cost of unsuper-vised manifold learning and preserving the embedding quality at the same time. An application to spectral clustering is also presented. Experimental results indicate that our multilevel approach is an appealing alternative to standard techniques.

Original languageEnglish (US)
Title of host publicationCIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops
Pages419-428
Number of pages10
DOIs
StatePublished - Dec 1 2010
Event19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 - Toronto, ON, Canada
Duration: Oct 26 2010Oct 30 2010

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
CountryCanada
CityToronto, ON
Period10/26/1010/30/10

Keywords

  • Manifold learning
  • Multilevel methods
  • Spectral clustering

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