Emilie Kaufmann

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Publications

Image document

Best-Arm Identification in Unimodal Bandits

Riccardo Poiani , Marc Jourdan , Emilie Kaufmann , Rémy Degenne
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics, May 2025, Phuket, Thailand
Communication dans un congrès hal-05125233 v1
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Pareto Set Identification With Posterior Sampling

Cyrille Kone , Marc Jourdan , Emilie Kaufmann
AISTATS 2025 - 28th International Conference on Artificial In- telligence and Statistic, May 2025, Phuket, Thailand
Communication dans un congrès hal-05125257 v1
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Bandit Pareto Set Identification in a Multi-Output Linear Model

Cyrille Kone , Emilie Kaufmann , Laura Richert
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics, May 2025, Phuket, Thailand
Communication dans un congrès hal-05125311 v1
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Constrained Pareto Set Identification with Bandit Feedback

Cyrille Kone , Emilie Kaufmann , Laura Richert
ICML 2025 - 42nd International Conference on Machine Learning, Jul 2025, Vancouver, Canada
Communication dans un congrès hal-05125339 v1
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Bandit Pareto Set Identification: the Fixed Budget Setting

Cyrille Kone , Emilie Kaufmann , Laura Richert
AISTATS 2024 - 27th International Conference on Artifi- cial Intelligence and Statistics, May 2024, Valencia, Spain
Communication dans un congrès hal-04877368 v1
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Optimal Multi-Fidelity Best-Arm Identification

Riccardo Poiani , Rémy Degenne , Emilie Kaufmann , Alberto Maria Metelli , Marcello Restelli
Advances in Neural Information Processing Systems (NeurIPS), Dec 2024, Vancouver (BC), Canada
Communication dans un congrès hal-04811199 v1
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Finding good policies in average-reward Markov Decision Processes without prior knowledge

Adrienne Tuynman , Rémy Degenne , Emilie Kaufmann
NeurIPS, Dec 2024, Vancouver (Canada), Canada
Communication dans un congrès hal-04809429 v1
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Power Mean Estimation in Stochastic Monte-Carlo Tree Search

Tuan Quang Tuan Dam , Odalric-Ambrym Maillard , Emilie Kaufmann
Uncertainty in Artificial Intelligence, Jul 2024, Barcelona, Spain
Communication dans un congrès hal-04714124 v1
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Dealing with Unknown Variances in Best-Arm Identification

Marc Jourdan , Rémy Degenne , Emilie Kaufmann
Algorithmic Learning Theory (ALT), Feb 2023, Singapore (SG), Singapore
Communication dans un congrès hal-04306221 v1
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An ε-Best-Arm Identification Algorithm for Fixed-Confidence and Beyond

Marc Jourdan , Rémy Degenne , Emilie Kaufmann
Advances in Neural Information Processing Systems (NeurIPS), Dec 2023, New Orleans, United States
Communication dans un congrès hal-04306214 v1
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Active Coverage for PAC Reinforcement Learning

Aymen Al-Marjani , Andrea Tirinzoni , Emilie Kaufmann
Conference on Learning Theory 2023, Jul 2023, Bangalore, India
Communication dans un congrès hal-04215441 v1
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Optimistic PAC Reinforcement Learning: the Instance-Dependent View

Andrea Tirinzoni , Aymen Al-Marjani , Emilie Kaufmann
Algorithmic Learning Theory (ALT), Feb 2023, Singapore (SG), Singapore
Communication dans un congrès hal-04306228 v1
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Adaptive Algorithms for Relaxed Pareto Set Identification

Cyrille Kone , Emilie Kaufmann , Laura Richert
NeurIPS 2023 - 37th Conference on Neural Information Processing Systems, Dec 2023, La Nouvelle Orléans, LA, United States
Communication dans un congrès hal-04306210 v1
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Near-Optimal Collaborative Learning in Bandits

Clémence Réda , Sattar Vakili , Emilie Kaufmann
NeurIPS 2022 - 36th Conference on Neural Information Processing System, Dec 2022, New Orleans, United States
Communication dans un congrès hal-03825099 v1
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Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs

Andrea Tirinzoni , Aymen Al-Marjani , Emilie Kaufmann
EWRL 2022 - European Workshop on Reinforcement Learning, Sep 2022, Milan, Italy
Communication dans un congrès hal-03767412 v1
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Top Two Algorithms Revisited

Marc Jourdan , Rémy Degenne , Dorian Baudry , Rianne de Heide , Emilie Kaufmann
NeurIPS 2022 - 36th Conference on Neural Information Processing System, Nov 2022, New Orleans, United States
Communication dans un congrès hal-03825103 v1
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Efficient Algorithms for Extreme Bandits

Dorian Baudry , Yoan Russac , Emilie Kaufmann
International conference on Artificial Intelligence and Statistics (AISTATS), Mar 2022, Virtual Conference, Spain
Communication dans un congrès hal-03741302 v1
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Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs

Andrea Tirinzoni , Aymen Al-Marjani , Emilie Kaufmann
NeurIPS 2022 - 36th Conference on Neural Information Processing System, Nov 2022, New Orleans, United States
Communication dans un congrès hal-03825101 v1
Image document

Optimistic PAC Reinforcement Learning: the Instance-Dependent View

Andrea Tirinzoni , Aymen Al-Marjani , Emilie Kaufmann
EWRL 2022 - European Workshop on Reinforcement Learning, Sep 2022, Milan, Italy
Communication dans un congrès hal-03767409 v1
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Episodic reinforcement learning in finite MDPs: Minimax lower bounds revisited

Omar Darwiche Domingues , Pierre Ménard , Emilie Kaufmann , Michal Valko
Algorithmic Learning Theory, Mar 2021, Paris / Virtual, France
Communication dans un congrès hal-03289004 v1
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Kernel-based reinforcement Learning: A finite-time analysis

Omar D Domingues , Pierre Ménard , Matteo Pirotta , Emilie Kaufmann , Michal Valko
International Conference on Machine Learning, Jul 2021, Vienna / Virtual, Austria
Communication dans un congrès hal-02541790 v2
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Fast active learning for pure exploration in reinforcement learning

Pierre Ménard , Omar Darwiche Domingues , Emilie Kaufmann , Anders Jonsson , Edouard Leurent et al.
International Conference on Machine Learning, Jul 2021, Vienna, Austria
Communication dans un congrès hal-02906985 v3
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Optimal Thompson Sampling strategies for support-aware CVaR bandits

Dorian Baudry , Romain Gautron , Emilie Kaufmann , Odalric-Ambrym Maillard
38th International Conference on Machine Learning, Jul 2021, Virtual, United States
Communication dans un congrès hal-03447244 v1
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A kernel-based approach to non-stationary reinforcement learning in metric spaces

Omar D Domingues , Pierre Ménard , Matteo Pirotta , Emilie Kaufmann , Michal Valko
International Conference on Artificial Intelligence and Statistics, Apr 2021, San Diego / Virtual, United States
Communication dans un congrès hal-03289026 v1
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Adaptive reward-free exploration

Emilie Kaufmann , Pierre Ménard , Omar Darwiche Domingues , Anders Jonsson , Edouard Leurent et al.
Algorithmic Learning Theory, 2021, Paris, France
Communication dans un congrès hal-02864574 v1
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Top-m identification for linear bandits

Clémence Réda , Emilie Kaufmann , Andrée Delahaye-Duriez
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021, Virtual, United States
Communication dans un congrès hal-03172145 v1
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Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling

Cindy Trinh , Emilie Kaufmann , Claire Vernade , Richard Combes
ALT 2020 - 31st International Conference on Algorithmic Learning Theory, Feb 2020, San Diego, United States. pp.1 - 28
Communication dans un congrès hal-02396943 v2
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Fixed-confidence guarantees for Bayesian best-arm identification

Xuedong Shang , Rianne de Heide , Emilie Kaufmann , Pierre Ménard , Michal Valko
International Conference on Artificial Intelligence and Statistics, 2020, Palermo, Italy
Communication dans un congrès hal-02330187 v2
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A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players

Etienne Boursier , Emilie Kaufmann , Abbas Mehrabian , Vianney Perchet
AISTATS 2020 - 23rd International Conference on Artificial Intelligence and Statistics, Aug 2020, Palermo, Italy
Communication dans un congrès hal-02006069 v3
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Planning in Markov Decision Processes with Gap-Dependent Sample Complexity

Anders Jonsson , Emilie Kaufmann , Pierre Ménard , Omar D Domingues , Edouard Leurent et al.
Neural Information Processing Systems, 2020, Vancouver, France
Communication dans un congrès hal-02863486 v2
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Sub-sampling for Efficient Non-Parametric Bandit Exploration

Dorian Baudry , Emilie Kaufmann , Odalric-Ambrym Maillard
NeurIPS 2020, Dec 2020, Vancouver, Canada
Communication dans un congrès hal-02977552 v1
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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, AutoML@ICML 2019 - 6th ICML Workshop on Automated Machine Learning, Jun 2019, Long Beach, United States
Communication dans un congrès hal-02145200 v1
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Analyse non asymptotique d'un test séquentiel de détection de rupture et application aux bandits non stationnaires

Lilian Besson , Emilie Kaufmann
GRETSI 2019 - XXVIIème Colloque francophone de traitement du signal et des images, Aug 2019, Lille, France
Communication dans un congrès hal-02152243 v1
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General parallel optimization without a metric

Xuedong Shang , Emilie Kaufmann , Michal Valko
Algorithmic Learning Theory, 2019, Chicago, United States
Communication dans un congrès hal-02047225 v2
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Multi-Armed Bandit Learning in IoT Networks: Learning helps even in non-stationary settings

Rémi Bonnefoi , Lilian Besson , Christophe Moy , Emilie Kaufmann , Jacques Palicot
CROWNCOM 2017 - 12th EAI International Conference on Cognitive Radio Oriented Wireless Networks, Sep 2017, Lisbon, Portugal. pp.173-185, ⟨10.1007/978-3-319-76207-4_15⟩
Communication dans un congrès hal-01575419 v2
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Corrupt Bandits for Preserving Local Privacy

Pratik Gajane , Tanguy Urvoy , Emilie Kaufmann
ALT 2018 - Algorithmic Learning Theory, Apr 2018, Lanzarote, Spain
Communication dans un congrès hal-01757297 v1
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Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling

Emilie Kaufmann , Wouter Koolen , Aurélien Garivier
Advances in Neural Information Processing Systems (NIPS), Dec 2018, Montréal, Canada
Communication dans un congrès hal-01804581 v1
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Adaptive black-box optimization got easier: HCT only needs local smoothness

Xuedong Shang , Emilie Kaufmann , Michal Valko
European Workshop on Reinforcement Learning, Oct 2018, Lille, France
Communication dans un congrès hal-01874637 v1
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Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence

Maryam Aziz , Jesse Anderton , Emilie Kaufmann , Javed Aslam
ALT 2018 - Algorithmic Learning Theory, Apr 2018, Lanzarote, Spain
Communication dans un congrès hal-01729969 v1
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Multi-Player Bandits Revisited

Lilian Besson , Emilie Kaufmann
Algorithmic Learning Theory, Mehryar Mohri; Karthik Sridharan, Apr 2018, Lanzarote, Spain
Communication dans un congrès hal-01629733 v2
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Aggregation of Multi-Armed Bandits Learning Algorithms for Opportunistic Spectrum Access

Lilian Besson , Emilie Kaufmann , Christophe Moy
IEEE WCNC - IEEE Wireless Communications and Networking Conference, Apr 2018, Barcelona, Spain. ⟨10.1109/wcnc.2018.8377070⟩
Communication dans un congrès hal-01705292 v1
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Monte-Carlo Tree Search by Best Arm Identification

Emilie Kaufmann , Wouter M. Koolen
NIPS 2017 - 31st Annual Conference on Neural Information Processing Systems, Dec 2017, Long Beach, United States. pp.1-23
Communication dans un congrès hal-01535907 v2
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Maximin Action Identification: A New Bandit Framework for Games

Aurélien Garivier , Emilie Kaufmann , Wouter M. Koolen
29th Annual Conference on Learning Theory (COLT), Jun 2016, New-York, United States
Communication dans un congrès hal-01273842 v2
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On Explore-Then-Commit Strategies

Aurélien Garivier , Emilie Kaufmann , Tor Lattimore
NIPS, Dec 2016, Barcelona, Spain
Communication dans un congrès hal-01322906 v2
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Optimal Best Arm Identification with Fixed Confidence

Aurélien Garivier , Emilie Kaufmann
29th Annual Conference on Learning Theory (COLT), Jun 2016, New York, United States
Communication dans un congrès hal-01273838 v2
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On the Complexity of A/B Testing

Emilie Kaufmann , Olivier Cappé , Aurélien Garivier
Conference on Learning Theory, Jun 2014, Barcelona, Spain. pp.461-481
Communication dans un congrès hal-00990254 v2

Thompson Sampling for one-dimensial exponential family bandits

Nathaniel Korda , Emilie Kaufmann , Rémi Munos
NIPS 2013 - Neural Information Processing Systems Conference, Dec 2013, Lake Tahoe, United States
Communication dans un congrès hal-02288407 v1

Information Complexity in Bandit Subset Selection

Emilie Kaufmann , Shivaram Kalyanakrishnan
Conference On Learning Theory, Jun 2013, Princeton, United States
Communication dans un congrès hal-02288406 v1
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Thompson sampling for one-dimensional exponential family bandits

Nathaniel Korda , Emilie Kaufmann , Rémi Munos
Advances in Neural Information Processing Systems, 2013, United States
Communication dans un congrès hal-00923683 v1

Thompson Sampling: An Asymptotically Optimal Finite Time Analysis

Emilie Kaufmann , Nathaniel Korda , Rémi Munos
ALT 2012 - International Conference on Algorithmic Learning Theory, Oct 2012, Lyon, France. pp.199-213, ⟨10.1007/978-3-642-34106-9_18⟩
Communication dans un congrès hal-00830033 v1

Thompson Sampling : an asymptotically optimal finite time analysis

Emilie Kaufmann , Nathaniel Korda , Rémi Munos
International Conference on Algorithmic Learning Theory, Nov 2012, Lyon, France. pp.199-213
Communication dans un congrès hal-02286442 v1

On Bayesian Upper Confidence Bounds for Bandit Problems

Emilie Kaufmann , Olivier Cappé , Aurélien Garivier
International Conference on Artificial Intelligence and Statistics (AISTAT), Apr 2012, La Palma, Iles Canaries, Spain. pp.592-600
Communication dans un congrès hal-02286440 v1
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Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits

Lilian Besson , Emilie Kaufmann , Odalric-Ambrym Maillard , Julien Seznec
Journal of Machine Learning Research, 2022
Article dans une revue hal-02006471 v3
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On Multi-Armed Bandit Designs for Dose-Finding Trials

Maryam Aziz , Emilie Kaufmann , Marie-Karelle Riviere
Journal of Machine Learning Research, 2021
Article dans une revue hal-02533297 v1
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Non-Asymptotic Sequential Tests for Overlapping Hypotheses and application to near optimal arm identification in bandit models

Aurélien Garivier , Emilie Kaufmann
Sequential Analysis, 2021, 40 (1), pp.61-96. ⟨10.1080/07474946.2021.1847965⟩
Article dans une revue hal-02123833 v2
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Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals

Emilie Kaufmann , Wouter M. Koolen
Journal of Machine Learning Research, 2021
Article dans une revue hal-01886612 v3
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Machine learning applications in drug development

Clémence Réda , Emilie Kaufmann , Andrée Delahaye-Duriez
Computational and Structural Biotechnology Journal, 2020, 18, pp.241-252. ⟨10.1016/j.csbj.2019.12.006⟩
Article dans une revue hal-02533303 v1
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Asymptotically Optimal Algorithms for Budgeted Multiple Play Bandits

Alexander Luedtke , Emilie Kaufmann , Antoine Chambaz
Machine Learning, 2019, 108 (11), pp.1919-1949. ⟨10.1007/s10994-019-05799-x⟩
Article dans une revue hal-01338733 v3
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On Bayesian index policies for sequential resource allocation

Emilie Kaufmann
Annals of Statistics, 2018, 46 (2), pp.842-865. ⟨10.1214/17-AOS1569⟩
Article dans une revue hal-01251606 v3
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A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks

Emilie Kaufmann , Thomas Bonald , Marc Lelarge
Theoretical Computer Science, 2018, 742, pp.3-26. ⟨10.1016/j.tcs.2017.12.028⟩
Article dans une revue hal-01163147 v3
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Learning the distribution with largest mean: two bandit frameworks

Emilie Kaufmann , Aurélien Garivier
ESAIM: Proceedings and Surveys, 2017, 60, pp.114 - 131. ⟨10.1051/proc/201760114⟩
Article dans une revue hal-01449822 v3
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On the Complexity of Best Arm Identification in Multi-Armed Bandit Models

Emilie Kaufmann , Olivier Cappé , Aurélien Garivier
Journal of Machine Learning Research, 2016, 17, pp.1-42
Article dans une revue hal-01024894 v2
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De l'échantillonnage adaptatif à la résolution de jeux

Nathanaël Fijalkow , Emilie Kaufmann
Informatique Mathématique Une photographie en 2022, 2022
Chapitre d'ouvrage hal-04152484 v1