Composite Kernel Learning - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue Machine Learning Année : 2010

Composite Kernel Learning

Résumé

The Support Vector Machine is an acknowledged powerful tool for building clas- sifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Multiple Kernel Learning enables to learn the kernel, from an ensemble of basis kernels, whose com- bination is optimized in the learning process. Here, we propose Composite Kernel Learning to address the situation where distinct components give rise to a group structure among ker- nels. Our formulation of the learning problem encompasses several setups, putting more or less emphasis on the group structure. We characterize the convexity of the learning problem, and provide a general wrapper algorithm for computing solutions. Finally, we illustrate the behavior of our method on multi-channel data where groups correspond to channels.
Fichier principal
Vignette du fichier
ckl.pdf (679.13 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00528981 , version 1 (23-10-2010)

Identifiants

Citer

Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy. Composite Kernel Learning. Machine Learning, 2010, 79 (1), pp.73-103. ⟨10.1007/s10994-009-5150-6⟩. ⟨hal-00528981⟩
258 Consultations
520 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More