Keyword: Self-Normalized

Publication in Journal - December, 2017
Learning the distribution with largest mean: two bandit frameworks
ESAIM: Proceedings and Surveys
Publication in Journal - January, 2016
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models
Journal of Machine Learning Research
Presentation - May, 2015
Optimism in Reinforcement Learning and Kullback-Leibler Divergence
Toulouse, CIMI IMPRECISE PROBABILITIES WORKSHOP
Presentation - October, 2014
Bandits for Exploration: Best Arm Identification and Discovery with Probabilistic Experts
Imperial College, Multi-armed bandits meeting http://wwwf.imperial.ac.uk/~amijatov/IP/lps.php
Presentation - June, 2014
Empirical Likelihood Upper Confidence Bounds For Bandit Models
Barcelona, Journées Statistiques du Sud 2014 7èmes Journées Statistiques du Sud
Publication in Conference - June, 2014
On the Complexity of A/B Testing
Conference On Learning Theory
Presentation - April, 2014
Empirical Likelihood for Optimistic Algorithms in Dynamic Resource Allocation
Paris X Nanterre ANR SPADRO kick-off meeting
Presentation - September, 2013
Informational Confidence Bounds for Self-Normalized Averages and Applications
Seville (Spain) 2013 IEEE Information Theory Workshop
Publication in Conference - September, 2013
Informational Confidence Bounds for Self-Normalized Averages and Applications
IEEE Information Theory Workshop
Publication in Journal - June, 2013
Kullback-Leibler Upper Confidence Bounds for Optimal Sequential Allocation
Annals of Statistics
Presentation - March, 2013
Dynamic resource allocation as an estimation problem
Fête Parisienne in Computation, Inference and Optimization in IHES (Bures sur Yvette)
Publication in Conference - April, 2012
On Bayesian Upper Confidence Bounds for Bandit Problems
International Conference on Artificial Intelligence and Statistics
Presentation - January, 2012
Apprentissage par renforcement et déviations auto-normalisées
Séminaire de statistiques de Toulouse , Séminaire parisien
Presentation - November, 2011
Analyses d'algorithmes pour l'estimation et l'optimisation stochastiques
Soutenance d'habilitation à diriger des recherches (HDR), Orsay
Other Publication - November, 2011
Analyse d'algorithmes pour l'estimation et l'optimisation stochastiques
Publication in Journal - November, 2011
Context Tree Selection: A Unifying View
Stochastic Processes and their Applications
Presentation - October, 2011
On Upper-Confidence Bound Policies for Non-stationary Bandit Problems
ALT 2011 (Espoo, Finlande)
Publication in Conference - October, 2011
On Upper-Confidence Bound Policies for Non-stationary Bandit Problems
Algorithmic Learning Theory
Presentation - July, 2011
The KL-UCB for bounded bandit problems, and beyond
Budapest, Hongrie COLT 2011, videolectures
Publication in Conference - July, 2011
The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond
Conference On Learning Theory
Presentation - June, 2011
L'algorithme KL-UBC pour les bandits bornés, et au delà, I3M (Montpellier) puis ENGREF, groupe de travail prévision,
Séminaire du I3M de Montpellier, puis ENGREF slideshare
Presentation - October, 2010
Reinforcement Learning and Self-Normalized Deviation Bounds
Séminaire du Numec, USP, Sao Paulo
Presentation - September, 2010
Arbres de Contextes Probabilisés
Journées MAS 2010, Toulouse
Publication in Conference - September, 2010
Optimism in Reinforcement Learning and Kullback-Leibler Divergence
Allerton Conference on Communication, Control, and Computing
Presentation - May, 2010
Optimism in Reinforcement Learning and Kullback-Leibler Divergence
Séminaire SMILE in Paris
Presentation - June, 2008
Stratégies UCB en environnement non stationnaire
European Workshop on Reinforcement Learning in Lille
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