Emilie Kaufmann

Institution	office	homepage	group
■ Inria	None	None	Former members of the LINCS

Books And Theses

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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

⇣	⇣	A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players, Abbas Mehrabian, Etienne Boursier, Emilie Kaufmann, Vianney Perchet, AISTATS 2020, Palermo, Italy
⇣	⇣	Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling, Cindy Trinh, Emilie Kaufmann, Claire Vernade, Richard Combes, ALT 2020, San Diego, United States
⇣	⇣	Fixed-confidence guarantees for Bayesian best-arm identification, Xuedong Shang, Rianne De Heide, Pierre Menard, Emilie Kaufmann, Michal Valko, AISTATS 2020, Palermo, Italy
⇣		Analyse non asymptotique d'un test séquentiel de détection de rupture et application aux bandits non stationnaires Non-asymptotic analysis of a sequential rupture detection test and its application to non-stationary bandits, Lilian Besson, Emilie Kaufmann, GRETSI 2019 - XXVIIème Colloque francophone de traitement du signal et des images 2019, Lille, France
⇣		A simple dynamic bandit algorithm for hyper-parameter tuning, Xuedong Shang, Emilie Kaufmann, Michal Valko, Workshop on Automated Machine Learning at International Conference on Machine Learning 2019, Long Beach, United States
⇣		General parallel optimization without a metric, Xuedong Shang, Emilie Kaufmann, Michal Valko, Algorithmic Learning Theory 2019, Chicago, United States
	⇣	General parallel optimization a without metric, Xuedong Shang, Emilie Kaufmann, Michal Valko, ALT 2019
⇣		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 Koolen, Aurelien Garivier, NeurIPS 2018, Montréal, Canada
⇣	⇣	Corrupt Bandits for Preserving Local Privacy, Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann, ALT 2018, Lanzarote, Spain
⇣	⇣	Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence, Maryam Aziz, Jesse Anderton, Emilie Kaufmann, Javed Aslam, ALT 2018, Lanzarote, Spain
⇣		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
	⇣	Aggregation of multi-armed bandits learning algorithms for opportunistic spectrum access, Lilian Besson, Emilie Kaufmann, Christophe Moy, WCNC 2018
⇣		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 Koolen, NIPS 2017, Long Beach, United States
⇣	⇣	Maximin Action Identification - A New Bandit Framework for Games, Aurelien Garivier, Emilie Kaufmann, Wouter Koolen, COLT 2016, New-York, United States
⇣	⇣	On Explore-Then-Commit strategies, Aurelien Garivier, Tor Lattimore, Emilie Kaufmann, NIPS 2016, Barcelona, Spain
⇣	⇣	Optimal Best Arm Identification with Fixed Confidence, Aurelien Garivier, Emilie Kaufmann, COLT 2016, New York, United States
⇣	⇣	On the Complexity of A/B Testing, Emilie Kaufmann ■, Olivier Cappe, Aurelien Garivier, COLT 2014, Barcelona, Spain
⇣		Thompson Sampling for one-dimensial exponential family bandits, Nathaniel Korda, Emilie Kaufmann, Rémi Munos, NIPS 2013 - Neural Information Processing Systems Conference 2013, Lake Tahoe, United States
⇣	⇣	Information Complexity in Bandit Subset Selection, Emilie Kaufmann, Shivaram Kalyanakrishnan, COLT 2013, Princeton, United States
⇣		Thompson sampling for one-dimensional exponential family bandits, Nathaniel Korda, Emilie Kaufmann, Rémi Munos, Advances in Neural Information Processing Systems 2013, United States
	⇣	Thompson Sampling for 1-Dimensional Exponential Family Bandits, Nathaniel Korda, Emilie Kaufmann, Remi Munos, NIPS 2013
⇣	⇣	Thompson Sampling - An Asymptotically Optimal Finite-Time Analysis, Emilie Kaufmann, Nathaniel Korda, Remi Munos, ALT 2012, Lyon, France
⇣	⇣	On Bayesian Upper Confidence Bounds for Bandit Problems, Emilie Kaufmann, Olivier Cappe, Aurelien Garivier, AISTATS 2012, La Palma, Iles Canaries, Spain

Journal articles

⇣		Machine learning applications in drug development, Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez, Computational and Structural Biotechnology Journal 2020
⇣	⇣	Asymptotically optimal algorithms for budgeted multiple play bandits, Alexander Luedtke, Emilie Kaufmann, Antoine Chambaz, Machine Learning 2019
⇣	⇣	A spectral algorithm with additive clustering for the recovery of overlapping communities in networks, Emilie Kaufmann, Thomas Bonald ■, Marc Lelarge ■, Theoretical Computer Science 2018
⇣		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 Cappe, Aurelien Garivier, Journal of Machine Learning Research 2016

Reports

⇣	⇣	Fast active learning for pure exploration in reinforcement learning, Pierre Menard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko, CoRR 2020
⇣	⇣	Adaptive Reward-Free Exploration, Emilie Kaufmann, Pierre Menard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko, CoRR 2020
⇣	⇣	Planning in Markov Decision Processes with Gap-Dependent Sample Complexity, Anders Jonsson, Emilie Kaufmann, Pierre Menard, Omar Darwiche Domingues, Edouard Leurent, Michal Valko, CoRR 2020
⇣	⇣	Regret Bounds for Kernel-Based Reinforcement Learning, Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko, CoRR 2020
	⇣	A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces, Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko, CoRR 2020
	⇣	New Algorithms for Multiplayer Bandits when Arm Means Vary Among Players, Emilie Kaufmann, Abbas Mehrabian, CoRR 2019
	⇣	The Generalized Likelihood Ratio Test meets klUCB - an Improved Algorithm for Piece-Wise Non-Stationary Bandits, Lilian Besson, Emilie Kaufmann, CoRR 2019
	⇣	On Multi-Armed Bandit Designs for Phase I Clinical Trials, Maryam Aziz, Emilie Kaufmann, Marie Karelle Riviere, CoRR 2019
⇣	⇣	Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals, Emilie Kaufmann, Wouter 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, Remi Bonnefoi, Lilian Besson, Christophe Moy, Emilie Kaufmann, Jacques Palicot, CoRR 2018
⇣	⇣	Learning the distribution with largest mean - two bandit frameworks, Emilie Kaufmann, Aurelien 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, Remi Munos, CoRR 2012

Misc

		⇣		On Multi-Armed Bandit Designs for Dose-Finding Trials, Maryam Aziz, Emilie Kaufmann, Marie-Karelle Riviere, 2020
		⇣		Non-Asymptotic Sequential Tests for Overlapping Hypotheses and application to near optimal arm identification in bandit models, Aurélien Garivier, Emilie Kaufmann, 2019
		⇣		The Generalized Likelihood Ratio Test meets klUCB: an Improved Algorithm for Piece-Wise Non-Stationary Bandits Le test du ratio de vraisemblance généralisé (GLRT) rencontre klUCB : un meilleur algorithme pour les bandits stationnaires par morceaux, Lilian Besson, Emilie Kaufmann, 2019
		⇣		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