Emilie Kaufmann

Publications

Communication dans un congrès (53)

DP-SPRT: Differentially Private Sequential Probability Ratio Tests Thomas Michel,Debabrota Basu,Emilie Kaufmann Twenty-Ninth Annual Conference on Artificial Intelligence and Statistics (AISTATS), May 2026, Tangier, Morocco. ⟨10.48550/arXiv.2508.06377⟩ Communication dans un congrès hal-05230052v1
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-05125233v1
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-05125257v1
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-05125311v1
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-05125339v1
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-04877368v1
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-04714124v1
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-04809429v1
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-04811199v1
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-04306221v1
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-04306214v1
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-04215441v1
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-04306228v1
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-04306210v1
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-03825099v1
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-03767412v1
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-03825103v1
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-03741302v1
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-03825101v1
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-03767409v1
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-03289004v1
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-02541790v2
Fast active learning for pure exploration in reinforcement learning Pierre Ménard,Omar Darwiche Domingues,Emilie Kaufmann,Anders Jonsson,Edouard Leurentet al. International Conference on Machine Learning, Jul 2021, Vienna, Austria Communication dans un congrès hal-02906985v3
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-03447244v1
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-03289026v1
Adaptive reward-free exploration Emilie Kaufmann,Pierre Ménard,Omar Darwiche Domingues,Anders Jonsson,Edouard Leurentet al. Algorithmic Learning Theory, 2021, Paris, France Communication dans un congrès hal-02864574v1
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-03172145v1
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-02330187v2
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-02396943v2
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-02006069v3
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity Anders Jonsson,Emilie Kaufmann,Pierre Ménard,Omar D Domingues,Edouard Leurentet al. Neural Information Processing Systems, 2020, Vancouver, France Communication dans un congrès hal-02863486v2
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-02977552v1
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-02145200v1
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-02152243v1
General parallel optimization without a metric Xuedong Shang,Emilie Kaufmann,Michal Valko Algorithmic Learning Theory, 2019, Chicago, United States Communication dans un congrès hal-02047225v2
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-01575419v2
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-01874637v1
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-01757297v1
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-01804581v1
Multi-Player Bandits Revisited Lilian Besson,Emilie Kaufmann Algorithmic Learning Theory, Mehryar Mohri; Karthik Sridharan, Apr 2018, Lanzarote, Spain Communication dans un congrès hal-01629733v2
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-01729969v1
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-01705292v1
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-01535907v2
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-01273842v2
On Explore-Then-Commit Strategies Aurélien Garivier,Emilie Kaufmann,Tor Lattimore NIPS, Dec 2016, Barcelona, Spain Communication dans un congrès hal-01322906v2
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-01273838v2
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-00990254v2
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-02288407v1
Information Complexity in Bandit Subset Selection Emilie Kaufmann,Shivaram Kalyanakrishnan Conference On Learning Theory, Jun 2013, Princeton, United States Communication dans un congrès hal-02288406v1
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-00923683v1
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-00830033v1
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-02286442v1
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-02286440v1

Article dans une revue (10)

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-02006471v3
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-02533297v1
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-02123833v2
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-01886612v3
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-02533303v1
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-01338733v3
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-01251606v3
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-01163147v3
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-01449822v3
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-01024894v2

Chapitre d'ouvrage (1)

De l'échantillonnage adaptatif à la résolution de jeux Nathanaël Fijalkow,Emilie Kaufmann Informatique Mathématique Une photographie en 2022, 2022 Chapitre d'ouvrage hal-04152484v1

HDR (1)

Contributions to the Optimal Solution of Several Bandit Problems Emilie Kaufmann Machine Learning [stat.ML]. Université de Lille, 2020 HDR tel-03825097v1

Pré-publication, Document de travail (1)

What Doubling Tricks Can and Can't Do for Multi-Armed Bandits Lilian Besson,Emilie Kaufmann 2018 Pré-publication, Document de travail hal-01736357v1

Thèse (1)

Analysis of bayesian and frequentist strategies for sequential resource allocation Emilie Kaufmann Machine Learning [cs.LG]. Télécom ParisTech, 2014. English. ⟨NNT : 2014ENST0056⟩ Thèse tel-01413183v1