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Equipe SEQUEL
Sequential Learning
Présentation / Membres / Thèses / Publications HAL
The aim of SequeL is to study the resolution of sequential decision problems. For that purpose, we study sequential learning algorithms. We put an emphasis on the use of concepts and tools drawn from statistical learning, namely kernel methods, and Bayesian estimation methods. We favor non parametric approaches. Our work spans from theory of learnability, to the design of efficient algorithm, to applications.
Site web :
Responsable :
- Philippe Preux (Professeur)
Agenda
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13 - 14 déc. 2012
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14 déc. 2012
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14 déc. 2012
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20 déc. 2012
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20 déc. 2012
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11 janv. 2013
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17 janv. 2013
Soutenances
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13 déc. 2012
Ours
UMR 8022 - Laboratoire d'Informatique Fondamentale de Lille - Copyright © 2012 Sophie TISON - Crédits & Mentions légales