PAC-Bayesian aggregation and multi-armed bandits

Abstract : This habilitation thesis presents several contributions to (1) the PAC-Bayesian analysis of statistical learning, (2) the three aggregation problems: given d functions, how to predict as well as (i) the best of these d functions (model selection type aggregation), (ii) the best convex combination of these d functions, (iii) the best linear combination of these d functions, (3) the multi-armed bandit problems.
Document type :
Habilitation à diriger des recherches
Statistics. Université Paris-Est, 2010


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Contributor : Jean-Yves Audibert <>
Submitted on : Monday, November 15, 2010 - 12:35:54 PM
Last modification on : Thursday, February 12, 2015 - 1:01:09 AM

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  • HAL Id : tel-00536084, version 1
  • ARXIV : 1011.3396

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Jean-Yves Audibert. PAC-Bayesian aggregation and multi-armed bandits. Statistics. Université Paris-Est, 2010. <tel-00536084>

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