Composite Kernel Learning - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2008

Composite Kernel Learning

Résumé

The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Multiple Kernel Learning (MKL) enables to learn the kernel, from an ensemble of basis kernels, whose combination 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 kernels. 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.

Domaines

Autres [stat.ML]
Fichier principal
Vignette du fichier
CKL.pdf (166.23 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-00316016 , version 1 (02-09-2008)

Identifiants

  • HAL Id : hal-00316016 , version 1

Citer

Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy. Composite Kernel Learning. International Conference on Machine Learning (ICML 2008), Jul 2008, Helsinki, Finland. pp.1040-1047. ⟨hal-00316016⟩
99 Consultations
90 Téléchargements

Partager

Gmail Facebook X LinkedIn More