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,
European Workshop on Reinforcement Learning 2018, Lille, France
⇣ ⇣ Sequential Test for the Lowest Mean - From Thompson to Murphy Sampling,
Emilie Kaufmann, Wouter M. Koolen, Aurélien Garivier,
NeurIPS 2018, Montréal, Canada, 6335-6345
⇣ ⇣ 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, Lyon, France, 199-213
⇣ On Bayesian Upper Confidence Bounds for Bandit Problems,
Emilie Kaufmann, Olivier Cappé, Aurélien Garivier,
AISTATS 2012, 592-600

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

⇣ ⇣ Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals,
Emilie Kaufmann, Wouter M. Koolen,
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
⇣ Thompson Sampling - An Optimal Finite Time Analysis,
Emilie Kaufmann, Nathaniel Korda, Rémi Munos,
CoRR 2012

Misc

⇣ 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