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ICML
2009
IEEE

Fast evolutionary maximum margin clustering

10 years 2 months ago
Fast evolutionary maximum margin clustering
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding an optimal partition of the data into two classes such that the margin induced by a subsequent application of a support vector machine is maximal. We propose a method based on stochastic search to address this hard optimization problem. While a direct implementation would be infeasible for large data sets, we present an efficient computational shortcut for assessing the “quality” of intermediate solutions. Experimental results show that our approach outperforms existing methods in terms of clustering accuracy.
Fabian Gieseke, Tapio Pahikkala, Oliver Kramer
Added 19 May 2010
Updated 19 May 2010
Type Conference
Year 2009
Where ICML
Authors Fabian Gieseke, Tapio Pahikkala, Oliver Kramer
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