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2009
Springer

Generalized Clustering via Kernel Embeddings

12 years 1 months ago
Generalized Clustering via Kernel Embeddings
Abstract. We generalize traditional goals of clustering towards distinguishing components in a non-parametric mixture model. The clusters are not necessarily based on point locations, but on higher order criteria. This framework can be implemented by embedding probability distributions in a Hilbert space. The corresponding clustering objective is very general and relates to a range of common clustering concepts.
Stefanie Jegelka, Arthur Gretton, Bernhard Sch&oum
Added 27 May 2010
Updated 27 May 2010
Type Conference
Year 2009
Where KI
Authors Stefanie Jegelka, Arthur Gretton, Bernhard Schölkopf, Bharath K. Sriperumbudur, Ulrike von Luxburg
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