People


Emilie Kaufmann

Institution Inria
GroupFormer members of the LINCS

Books And Theses

Analysis of bayesian and frequentist strategies for sequential resource allocation Analyse de stratégies bayésiennes et fréquentistes pour l'allocation séquentielle de ressources,
Emilie Kaufmann ,
2014
Analysis of bayesian and frequentist strategies for sequential resource allocation. (Analyse de stratégies bayésiennes et fréquentistes pour l'allocation séquentielle de ressources),
Emilie Kaufmann ,
2014

Articles

Adaptive black-box optimization got easier: HCT only needs local smoothness,
Xuedong Shang, Emilie Kaufmann, Michal Valko,
EWRL 2018 - 14th European Workshop on Reinforcement Learning 2018, Lille, France
Corrupt Bandits for Preserving Local Privacy,
Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann,
ALT 2018, Lanzarote, Spain, 387-412
Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence,
Maryam Aziz, Jesse Anderton, Emilie Kaufmann, Javed A. Aslam,
ALT 2018, Lanzarote, Spain, 3-24
Multi-Player Bandits Revisited Modèles de Bandits Multi-Joueurs Revisités,
Lilian Besson, Emilie Kaufmann,
Algorithmic Learning Theory 2018, Lanzarote, Spain
Aggregation of Multi-Armed Bandits Learning Algorithms for Opportunistic Spectrum Access Agrégation d'algorithmes d'apprentissage pour les bandits multi-bras appliquée à l'accès opportuniste au spectre,
Lilian Besson, Emilie Kaufmann, Christophe Moy,
IEEE WCNC - IEEE Wireless Communications and Networking Conference 2018, Barcelona, Spain
{Multi-Player Bandits Revisited},
Lilian Besson, Emilie Kaufmann,
ALT 2018, 56-92
Aggregation of multi-armed bandits learning algorithms for opportunistic spectrum access,
Lilian Besson, Emilie Kaufmann, Christophe Moy,
WCNC 2018, 1-6
Multi-Armed Bandit Learning in IoT Networks: Learning helps even in non-stationary settings Apprentissage de Bandit Multi-Bras dans les réseaux Internet des Objets: l'apprentissage est utile même dans des cas non-stationnaires,
Rémi Bonnefoi, Lilian Besson, Christophe Moy, Emilie Kaufmann, Jacques Palicot,
CROWNCOM 2017 - 12th EAI International Conference on Cognitive Radio Oriented Wireless Networks 2017, Lisbon, Portugal
Monte-Carlo Tree Search by Best Arm Identification,
Emilie Kaufmann, Wouter M. Koolen,
NIPS 2017, Long Beach, United States, 4904-4913
Maximin Action Identification - A New Bandit Framework for Games,
Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen,
COLT 2016, New-York, United States, 1028-1050
On Explore-Then-Commit strategies,
Aurélien Garivier, Tor Lattimore, Emilie Kaufmann,
NIPS 2016, Barcelona, Spain, 784-792
Optimal Best Arm Identification with Fixed Confidence,
Aurélien Garivier, Emilie Kaufmann,
COLT 2016, New York, United States, 998-1027
On the Complexity of A/B Testing,
Emilie Kaufmann , Olivier Cappé, Aurélien Garivier,
COLT 2014, Barcelona, Spain, 461-481
Thompson sampling for one-dimensional exponential family bandits,
Nathaniel Korda, Emilie Kaufmann, Rémi Munos,
Advances in Neural Information Processing Systems 2013, United States
Information Complexity in Bandit Subset Selection,
Emilie Kaufmann, Shivaram Kalyanakrishnan,
COLT 2013, 228-251
Thompson Sampling for 1-Dimensional Exponential Family Bandits,
Nathaniel Korda, Emilie Kaufmann, Rémi Munos,
NIPS 2013, 1448-1456
Thompson Sampling: An Asymptotically Optimal Finite Time Analysis,
Emilie Kaufmann, Nathaniel Korda, Rémi Munos,
ALT 2012 - International Conference on Algorithmic Learning Theory 2012, Lyon, France

Journal articles

A spectral algorithm with additive clustering for the recovery of overlapping communities in networks,
Emilie Kaufmann, Thomas Bonald , Marc Lelarge ,
Theoretical Computer Science 2018, 3-26
On Bayesian index policies for sequential resource allocation,
Emilie Kaufmann,
Annals of Statistics 2017
On the Complexity of Best-Arm Identification in Multi-Armed Bandit Models,
Emilie Kaufmann, Olivier Cappé, Aurélien Garivier,
Journal of Machine Learning Research 2016, 1:1-1:42

Reports

Sequential Test for the Lowest Mean - From Thompson to Murphy Sampling,
Emilie Kaufmann, Wouter M. Koolen, Aurélien Garivier,
CoRR 2018
What Doubling Tricks Can and Can't Do for Multi-Armed Bandits,
Lilian Besson, Emilie Kaufmann,
CoRR 2018
Multi-Armed Bandit Learning in IoT Networks - Learning helps even in non-stationary settings,
Rémi Bonnefoi, Lilian Besson, Christophe Moy, Emilie Kaufmann, Jacques Palicot,
CoRR 2018
Learning the distribution with largest mean - two bandit frameworks,
Emilie Kaufmann, Aurélien Garivier,
ESAIM: Proceedings and Surveys 2017
Corrupt Bandits for Privacy Preserving Input,
Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann,
CoRR 2017
Multi-Player Bandits Models Revisited,
Lilian Besson, Emilie Kaufmann,
CoRR 2017
Asymptotically Optimal Algorithms for Multiple Play Bandits with Partial Feedback,
Alexander Luedtke, Emilie Kaufmann, Antoine Chambaz,
CoRR 2016

Misc

Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals,
Emilie Kaufmann, Wouter Koolen,
2018
What Doubling Tricks Can and Can't Do for Multi-Armed Bandits Ce que peuvent et ne peuvent pas faire les astuces de doublement pour les bandits multi-bras,
Lilian Besson, Emilie Kaufmann,
2018
Asymptotically Optimal Algorithms for Budgeted Multiple Play Bandits,
Alexander Luedtke, Emilie Kaufmann, Antoine Chambaz,
2017