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An Equivalence between the Lasso and Support Vector Machines

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SimpleMKL

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 kernel learning algorithm, based on semi-infinite linear ...

2008

Numerical methods and models relevant to transportation applications

Michaël Clément Louis Ghislain Thémans

In this thesis, we focus on standard classes of problems in numerical optimization: unconstrained nonlinear optimization as well as systems of nonlinear equations. More precisely, we consider two types of unconstrained nonlinear optimization problems. On t ...

EPFL2007

Prior Knowledge in Kernel Methods

Alexei Pozdnoukhov

Machine Learning is a modern and actively developing field of computer science, devoted to extracting and estimating dependencies from empirical data. It combines such fields as statistics, optimization theory and artificial intelligence. In practical task ...

École Polytechnique Fédérale de Lausanne2006

Prior knowledge in Kernel methods

Alexei Pozdnoukhov

EPFL2006

Differential Evolution applied to a multimodal information theoretic optimization problem

Jean-Marc Vesin, Murat Kunt, Vlad Popovici, Patricia Besson

This paper discusses the problems raised by the optimization of a mutual information-based objective function, in the context of a multimodal speaker detection. As no approximation is used, this function is highly nonlinear and plagued by numerous local mi ...

2006

Extraction of Audio Features Specific to Speech using Information Theory and Differential Evolution

Jean-Philippe Thiran, Jean-Marc Vesin, Murat Kunt, Vlad Popovici, Patricia Besson

We present a method that exploits an information theoretic framework to extract optimized audio features using the video information. A simple measure of mutual information (MI) between the resulting audio features and the video ones allows to detect the a ...

2005

Trust-region methods based on radial basis functions with application to biomedical imaging

Rodrigue Oeuvray

We have developed a new derivative-free algorithm based on Radial Basis Functions (RBFs). Derivative-free optimization is an active field of research and several algorithms have been proposed recently. Problems of this nature in the industrial setting are ...

EPFL2005

A uniqueness result concerning a robust regularized least-squares solution

Ali H. Sayed

In solving a robust version of regularized least squares with weighting, a certain scalar-valued optimization problem is required in order to determine the regularized robust solution and the corresponding robustified weighting parameters. This letter esta ...

Elsevier2002

Face Verification using MLP and SVM

Sébastien Marcel

The performance of machine learning algorithms has steadily improved over the past few years, such as MLP or more recently SVM. In this paper, we compare two successful discriminant machine learning algorithms apply to the problem of face verification: MLP ...

IDIAP2002

Face Verification using MLP and SVM

Sébastien Marcel

2002