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Y.: SimpleMKL

• Alain Rakotomamonjy, Francis Bach, Stéphane Canu, Yves Grandvalet
• 2008

Multiple kernel learning aims at simultaneously learning a kernel and the associated predictor in supervised learning settings. For the support vector machine, an efficient and general multiple… (More)

Journal of Machine Learning Research X (2008) 1-34 Submitted 01/08; Revised 08/08; Published XX/XX

• Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet
• 2008

Multiple kernel learning (MKL) aims at simultaneously learning a kernel and the associated predictor in supervised learning settings. For the support vector machine, an efficient and general multiple… (More)

More efficiency in multiple kernel learning

• Alain Rakotomamonjy, Francis R. Bach, Stéphane Canu, Yves Grandvalet
• ICML
• 2007

An efficient and general multiple kernel learning (MKL) algorithm has been recently proposed by Sonnenburg et al. (2006). This approach has opened new perspectives since it makes the MKL approach… (More)

Training Invariant Support Vector Machines using Selective Sampling

• Gaëlle Loosli, Stéphane Canu, Léon Bottou
• 2005

author?) [3] describe the efficient online LASVM algorithm using selective sampling. On the other hand, (author?) [24] propose a strategy for handling invariance in SVMs, also using selective… (More)

Recovering Sparse Signals With a Certain Family of Nonconvex Penalties and DC Programming

• Gilles Gasso, Alain Rakotomamonjy, Stéphane Canu
• IEEE Transactions on Signal Processing
• 2009

This paper considers the problem of recovering a sparse signal representation according to a signal dictionary. This problem could be formalized as a penalized least-squares problem in which sparsity… (More)

Adaptive Scaling for Feature Selection in SVMs

• Yves Grandvalet, Stéphane Canu
• NIPS
• 2002

This paper introduces an algorithm for the automatic relevance determination of input variables in kernelized Support Vector Machines. Relevance is measured by scale factors defining the input space… (More)

Learning with non-positive kernels

• Cheng Soon Ong, Xavier Mary, Stéphane Canu, Alexander J. Smola
• ICML
• 2004

In this paper we show that many kernel methods can be adapted to deal with indefinite kernels, that is, kernels which are not positive semidefinite. They do not satisfy Mercer's condition and they… (More)

Kernel Basis Pursuit

• Vincent Guigue, Alain Rakotomamonjy, Stéphane Canu
• CAP
• 2005

Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but every problem leads to two major… (More)

Molecular characterization of Echinococcus granulosus in sheep and goats of Peloponnesus, Greece

• A Varcasia, Stéphane Canu, +4 authors Aristarchos M Seimenis
• Parasitology Research
• 2007

Although cystic echinococcosis (CE) has been a recognized public health problem in Greece, molecular data are lacking regarding the types and prevalences of infecting strains of the etiological agent… (More)

Comments on the "Core Vector Machines: Fast SVM Training on Very Large Data Sets"

• Gaëlle Loosli, Stéphane Canu
• Journal of Machine Learning Research
• 2007

In a recently published paper in JMLR, Tsang et al. (2005) present an algorithm for SVM called Core Vector Machines (CVM) and illustrate its performances through comparisons with other SVM solvers.… (More)

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