SVM and kernel machines - CEL - Cours en ligne Access content directly
Lectures Year : 2011

SVM and kernel machines


Kernel Machines is a term covering a large class of learning algorithms, including Splines and support vector machines (SVM) as a particular instance. Kernel Machines is an important and active field of all Machine Learning research. Not only the number of publications bear witness of this fact but also the high quality of the results obtained by kernel machines in recent pattern recognition competitions. This tutorial will provide an introduction to kernel machines by explaining how and why it works. It will be organized in three parts dealing with the problem: kernels and learning (part 1), tools: kernels, functions, costs and optimization (part 2), and algorithms for non sparse and sparse kernel machines (part 3).
Fichier principal
Vignette du fichier
tutorial_04_Kernel_Advances.pdf (1.08 Mo) Télécharger le fichier
Homework.pdf (75.95 Ko) Télécharger le fichier
tutorial_01.pdf (641.57 Ko) Télécharger le fichier
tutorial_02_Noyaux.pdf (555.7 Ko) Télécharger le fichier
tutorial_03_kernel_machines.pdf (1.83 Mo) Télécharger le fichier

Dates and versions

cel-00643485 , version 1 (22-11-2011)


  • HAL Id : cel-00643485 , version 1


Stéphane Canu, Gaëlle Loosli, Alain Rakotomamonjy. SVM and kernel machines. École thématique. SVM and kernel machines, ECI 2011, Buenos Aires, 2011, pp.100. ⟨cel-00643485⟩
1111 View
1311 Download


Gmail Facebook X LinkedIn More