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- L. Birge, Pascal Massart, P. Massart
- 2004

This paper is mainly devoted to a precise analysis of what kind of penalties should be used in order to perform model selection via the minimization of a penalized least-squares type criterion within… (More)

We propose a general theorem providing upper bounds for the risk of an empirical risk minimizer (ERM).We essentially focus on the binary classi
cation framework. We extend Tsybakovs analysis of the… (More)

- Pascal Massart
- 2005

L’accès aux archives de la revue « Annales de la faculté des sciences de Toulouse » (http://picard.ups-tlse.fr/∼annales/), implique l’accord avec les conditions générales d’utilisation… (More)

- Stéphane Boucheron, Gábor Lugosi, Pascal Massart
- Random Struct. Algorithms
- 2000

We present a new general concentration-of-measure inequality and illustrate its power by applications in random combinatorics. The results nd direct applications in some problems of learning theory.… (More)

- Sylvain Arlot, Pascal Massart
- Journal of Machine Learning Research
- 2009

Penalization procedures often suffer from their dependence on multiplying factors, whose optimal values are either unknown or hard to estimate from the data. We propose a completely data-driven… (More)

We investigate a new methodology, worked out by Ledoux and Mas-sart, to prove concentration-of-measure inequalities. The method is based on certain modified logarithmic Sobolev inequalities. We… (More)

- Pascal Massart, P. Massart
- 2008

The support vector machine (SVM) algorithm is well known to the computer learning community for its very good practical results. The goal of the present paper is to study this algorithm from a… (More)

A general method for obtaining moment inequalities for functions of independent random variables is presented. It is a generalization of the entropy method which has been used to derive concentration… (More)

- Laurent Zwald, Régis Vert, Gilles Blanchard, Pascal Massart
- NIPS
- 2004

This paper investigates the effect of Kernel Principal Component Analysis (KPCA) within the classification framework, essentially the regularization properties of this dimensionality reduction… (More)

- Pascal Massart, P. Massart
- 2006

These last years, much attention has been paid to the construction of model selection criteria via penalization. Vladimir Koltchinskii has to be congratulated for providing a theory reaching a level… (More)