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Regularizing multiple kernel learning using response surface methodology Mehmet Gonen , Ethem Alpaydin
 

Summary: Regularizing multiple kernel learning using response surface methodology
Mehmet G¨onen Ã, Ethem Alpaydin
Department of Computer Engineering, Bogazic-i University, TR-34342 Bebek, _Istanbul, Turkey
a r t i c l e i n f o
Article history:
Received 26 June 2009
Received in revised form
12 May 2010
Accepted 2 July 2010
Keywords:
Support vector machine
Multiple kernel learning
Regularization
Response surface methodology
a b s t r a c t
In recent years, several methods have been proposed to combine multiple kernels using a weighted
linear sum of kernels. These different kernels may be using information coming from multiple sources
or may correspond to using different notions of similarity on the same source. We note that such
methods, in addition to the usual ones of the canonical support vector machine formulation, introduce
new regularization parameters that affect the solution quality and, in this work, we propose to optimize

  

Source: Alpaydın, Ethem - Department of Computer Engineering, Bogaziçi University

 

Collections: Computer Technologies and Information Sciences