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SVM and kernel machines

Abstract : 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).
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Contributor : Stephane Canu Connect in order to contact the contributor
Submitted on : Tuesday, November 22, 2011 - 10:40:29 AM
Last modification on : Wednesday, March 2, 2022 - 10:10:08 AM
Long-term archiving on: : Friday, November 16, 2012 - 11:40:31 AM


  • 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⟩



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