Keyword: Bandit Problems

Publication in Journal - May, 2019
Non-Asymptotic Sequential Tests for Overlapping Hypotheses and application to near optimal arm identification in bandit models
Publication in Conference - April, 2019
X-Armed Bandits: Optimizing Quantiles and Other Risks
Publication in Conference - December, 2018
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling
Neural Information Processing Systems
Presentation - November, 2018
Complexity of Sequential Decision Problems
ENS Lyon, Théminaire Théminaire de l'ENS Lyon
Publication in Conference - November, 2018
Profitable Bandits
Asian Conference on Machine Learning
Presentation - October, 2018
Introduction à certains problèmes de décisions séquentielles
Rencontre des Statisticiens Lyonnais (RSL), Campus de La Doua
Presentation - October, 2018
Comment les maths peuvent-elles aider les machines à apprendre ?
ENS Lyon, Journée de rentrée de l'UMPA
Publication in Journal - September, 2018
Explore First, Exploit Next: The True Shape of Regret in Bandit Problems
Mathematics of Operations Research
Publication in Conference - August, 2018
Optimization of a SSP's Header Bidding Strategy using Thompson Sampling
Special Interest Group on Knowledge Discovery and Data Mining
Presentation - May, 2018
Missing Mass, and Optimal Discovery
ENS Lyon Laboratoire de l'Informatique du Parallélisme
Publication in Journal - May, 2018
KL-UCB-switch: optimal regret bounds for stochastic bandits from both a distribution-dependent and a distribution-free viewpoints
Presentation - April, 2018
Minimisation du regret pour des bandits non-paramétriques grâce à la méthode de la vraisemblance empirique
ENS Lyon Séminaire de l'UMPA
Publication in Journal - December, 2017
Learning the distribution with largest mean: two bandit frameworks
ESAIM: Proceedings and Surveys
Publication in Conference - October, 2017
Thresholding Bandit for Dose-ranging: The Impact of Monotonicity
Publication in Conference - October, 2017
A minimax and asymptotically optimal algorithm for stochastic bandits
Algorithmic Learning Theory
Publication in Conference - September, 2017
Max K-armed bandits: On the ExtremeHunter algorithm and beyond
European Conference on Machine Learning
Presentation - July, 2017
The Complexity of Best-Arm Identification
Barcelona, FoCM2017 Workshop on Stochastic Computation
Publication in Journal - March, 2017
Diversified Bandit: the k-diversified Multiple-Play Recommendation Algorithm
Publication in Journal - March, 2017
Les systèmes de recommandations en ligne
Les Big Data à Découvert, Editions CNRS
Publication in Conference - December, 2016
On Explore-Then-Commit Strategies
Neural Information Processing Systems
Presentation - August, 2016
Sur la complexité de l'identification du meilleur bras sous contrainte de risque dans un modèle de bandits
Grenoble, Journées MAS 2016 Journées MAS 2016
Publication in Conference - July, 2016
Algorithme de bandit et obsolescence : un modèle pour la recommandation
Conférence Francophone sur l'Apprentissage Automatique
Presentation - June, 2016
Optimal Best Arm Identification with Fixed Confidence
New York COLT 2016, videolectures
Presentation - June, 2016
On the Complexity of Best Arm Identification with Fixed Confidence
Séminaire Pluridisciplinaire d'Optimisation de Toulouse SPOT
Publication in Conference - June, 2016
Optimal Best Arm Identification with Fixed Confidence
Conference On Learning Theory
Publication in Conference - June, 2016
Maximin Action Identification: A New Bandit Framework for Games
Conference On Learning Theory
Presentation - May, 2016
Recent advances in the understanding of bandit models
Grenoble, rencontres ANR ALICIA
Presentation - May, 2016
De l'intérêt des méthodes séquentielles (une introduction)
Toulouse, rencontres ANR SPADRO
Presentation - March, 2016
Sequential Optimization and Computer Experiments
Toulouse MASCOT-NUM 2016 Meeting
Presentation - January, 2016
Optimal Discovery with Probabilistic Expert Advice
Lancaster University, UK Multi-armed Bandit Workshop 2016 at STOR-i
Publication in Journal - January, 2016
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models
Journal of Machine Learning Research
Presentation - June, 2015
Systèmes de recommandation et algorithmes de bandits: notebook ipython pour l'enseignement
Lille, JDS 47èmes Journées de Statistique de la SFdS
Publication in Conference - May, 2015
A Multiple-play Bandit Algorithm Applies to Recommender Systems
Florida Artificial Intelligence Research Society Conference
Publication in Conference - March, 2015
Algorithmes de bandit pour les systèmes de recommandation : le cas de multiples recommandations simultanées
Conférence en Recherche d’Information et Applications
Presentation - March, 2015
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models
Berkeley Information Theory, Learning and Big Data Workshop, Simons Institute, youtube presentation
Publication in Journal - February, 2015
Algorithmes de bandits pour la recommandation à tirages multiples
Document numérique (Hermès)
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 - October, 2014
Allocation dynamique de ressources et modèles de bandits
Toulouse School of Economics, UT1 séminaire MAD
Presentation - September, 2014
Allocation dynamique de ressources et modèles de bandits
INRA Toulouse Séminaire MIAT
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 - April, 2014
Optimistic Solutions for Dynamic Resource Allocation
Paris (AgroParisTech) StatLearn 2014
Presentation - December, 2013
Optimal Discovery with Probabilistic Expert Advice: Finite Time Analysis and Macroscopic Optimality
CIRM, Rencontres de Statistique Mathématique "Mathematical Statistics with Applications in Mind" site web, Programme de la rencontre
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 - May, 2013
Quelques idées sur les problèmes de bandits
Mini-colloque LPT-IMT 2013, Séminaire de l'équipe GEPETTO (LAAS Toulouse)
Presentation - March, 2013
Dynamic resource allocation as an estimation problem
Fête Parisienne in Computation, Inference and Optimization in IHES (Bures sur Yvette)
Presentation - February, 2013
Problèmes de décisions séquentielles
plusieurs exposés dans le cadre du groupe de travail co-organisé avec Sébastien Gerchinovitz à l'IMT
Publication in Journal - February, 2013
Optimal Discovery with Probabilistic Expert Advice: Finite Time Analysis and Macroscopic Optimality
Journal of Machine Learning Research
Publication in Conference - December, 2012
Optimal Discovery with Probabilistic Expert Advice
IEEE Conference on Decision and Control
Presentation - November, 2012
Extraction d'information en grandes dimensions & allocation dynamique de ressources
avec Jean-Michel Loubès Séminaire FREMIT
Presentation - July, 2012
Problèmes de bandits et estimation
Séminaire de recherche du département TSI de Telecom ParisTech
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 - December, 2011
Exploration optimale à l'aide d'experts probabilistes
Séminaire du CMAP (Ecole Polytechnique, Palaiseau)
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
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
Publication in Conference - December, 2010
Parametric Bandits: The Generalized Linear Case
Neural Information Processing Systems
Presentation - October, 2010
Reinforcement Learning and Self-Normalized Deviation Bounds
Séminaire du Numec, USP, Sao Paulo
Publication in Conference - June, 2010
Bandits contextuels: apprentissage par renforcement dans les modèles linéaires généralisés
Journées Francophones Planification, Décision, et Apprentissage pour la conduite de systèmes
Presentation - March, 2010
Présentation de l'équipe et de l'apprentissage par renforcement
Evaluation AERES de l'équipe STA du LTCI à Telecom ParisTech, avec François Roueff
Presentation - June, 2008
Stratégies UCB en environnement non stationnaire
European Workshop on Reinforcement Learning in Lille
Subscribe to Keyword: Bandit Problems