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Sequential Learning
Presentation / Members / 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.
14 Feb 2013
14 Mar 2013
21 Mar 2013
4 Apr 2013
1 - 5 Jul 2013
18 Feb 2013
UMR 8022 - Laboratoire d'Informatique Fondamentale de Lille - Copyright © 2012 Sophie TISON - Crédits & Mentions légales
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