Séminaire de Probabilités et statistique

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Laboratoire de mathématiques et de leurs applications (LMAP)

Contacts

Directeur du LMAP

Gilles CARBOU

gilles.carbou@univ-pau.fr (gilles.carbou @ univ-pau.fr)

 

Gestion administrative

gestion-lmap@univ-pau.fr (gestion-lmap @ univ-pau.fr)

 

Secrétariat

secretariat-lmap@univ-pau.fr (secretariat-lmap @ univ-pau.fr)

Tél : 05 59 40 75 13
      05 59 40 74 32

Fax : 05 59 40 75 55

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Séminaire de Probabilités et statistique

Le séminaire a généralement lieu le jeudi, de 14h00 à 15h00, dans la salle de réunion de l'IUT STID (1er étage) et en visio avec la côte Basque

Organisateurs : Simplice Dossou-Gbété et Ghislain Verdier.

 

Prochainement : Camilo Broc (LMAP - UPPA)

Le 25-10-2018

Titre : Sparse Partial Least Square for structured data

 

Résumé : Nowadays, data analysis applied to high dimension has arisen. The edification of high dimensional data can be achieved by the gathering of different independent data. However each independant set can introduce its own bias. We can cope with this bias introducing the observation set structure into our model. The goal of this article is to build theoretical background for the dimension reduction method sparse Partial Least Square (sPLS) in the context of data presenting such an observation set structure. The innovation consist in building different sPLS models and linking them through a common-Lasso penalization. This theory could be applied to any field where observation present this kind of structure and therefore improve the sparse Partial Least Square in domains where it is competitive. Furthermore it can be extended to the
 articular case where variables can be gathered in given a priori groups, where sparse Partial Least Square is defined as a sparse group Partial Least Square. This work have been done under the supervision of Benoit Liquet and Borja Calvo.

 

 

Le programme de 2018