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ORCIDEmilie Kaufmann
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2020 – today
- 2024
[c41]Cyrille Kone, Emilie Kaufmann, Laura Richert:
Bandit Pareto Set Identification: the Fixed Budget Setting. AISTATS 2024: 2548-2556- [c40]Riccardo Poiani, Rémy Degenne, Emilie Kaufmann, Alberto Maria Metelli, Marcello Restelli:
Optimal Multi-Fidelity Best-Arm Identification. NeurIPS 2024 - [c39]Adrienne Tuynman, Rémy Degenne, Emilie Kaufmann:
Finding good policies in average-reward Markov Decision Processes without prior knowledge. NeurIPS 2024 - [i46]Adrienne Tuynman, Rémy Degenne, Emilie Kaufmann:
Finding good policies in average-reward Markov Decision Processes without prior knowledge. CoRR abs/2405.17108 (2024) - [i45]Tuan Dam, Odalric-Ambrym Maillard, Emilie Kaufmann:
Power Mean Estimation in Stochastic Monte-Carlo Tree_Search. CoRR abs/2406.02235 (2024) - [i44]Riccardo Poiani, Rémy Degenne, Emilie Kaufmann, Alberto Maria Metelli, Marcello Restelli:
Optimal Multi-Fidelity Best-Arm Identification. CoRR abs/2406.03033 (2024) - [i43]Riccardo Poiani, Marc Jourdan, Emilie Kaufmann, Rémy Degenne:
Best-Arm Identification in Unimodal Bandits. CoRR abs/2411.01898 (2024) - [i42]Cyrille Kone, Marc Jourdan, Emilie Kaufmann:
Pareto Set Identification With Posterior Sampling. CoRR abs/2411.04939 (2024) - 2023
- [c38]Marc Jourdan, Rémy Degenne, Emilie Kaufmann:
Dealing with Unknown Variances in Best-Arm Identification. ALT 2023: 776-849 - [c37]Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann:
Optimistic PAC Reinforcement Learning: the Instance-Dependent View. ALT 2023: 1460-1480 - [c36]Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann:
Active Coverage for PAC Reinforcement Learning. COLT 2023: 5044-5109 - [c35]Marc Jourdan, Rémy Degenne, Emilie Kaufmann:
An ε-Best-Arm Identification Algorithm for Fixed-Confidence and Beyond. NeurIPS 2023 - [c34]Cyrille Kone, Emilie Kaufmann, Laura Richert:
Adaptive Algorithms for Relaxed Pareto Set Identification. NeurIPS 2023 - [i41]Marc Jourdan, Rémy Degenne, Emilie Kaufmann:
An ε-Best-Arm Identification Algorithm for Fixed-Confidence and Beyond. CoRR abs/2305.16041 (2023) - [i40]Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann:
Active Coverage for PAC Reinforcement Learning. CoRR abs/2306.13601 (2023) - [i39]Cyrille Kone, Emilie Kaufmann, Laura Richert:
Adaptive Algorithms for Relaxed Pareto Set Identification. CoRR abs/2307.00424 (2023) - [i38]Cyrille Kone, Emilie Kaufmann, Laura Richert:
Bandit Pareto Set Identification: the Fixed Budget Setting. CoRR abs/2311.03992 (2023) - [i37]Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann:
Towards Instance-Optimality in Online PAC Reinforcement Learning. CoRR abs/2311.05638 (2023) - 2022
- [j6]Lilian Besson, Emilie Kaufmann, Odalric-Ambrym Maillard, Julien Seznec:
Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits. J. Mach. Learn. Res. 23: 77:1-77:40 (2022) - [c33]Dorian Baudry, Yoan Russac, Emilie Kaufmann:
Efficient Algorithms for Extreme Bandits. AISTATS 2022: 2210-2248 - [c32]Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide, Emilie Kaufmann:
Top Two Algorithms Revisited. NeurIPS 2022 - [c31]Clémence Réda, Sattar Vakili, Emilie Kaufmann:
Near-Optimal Collaborative Learning in Bandits. NeurIPS 2022 - [c30]Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann:
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs. NeurIPS 2022 - [i36]Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann:
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs. CoRR abs/2203.09251 (2022) - [i35]Dorian Baudry, Yoan Russac, Emilie Kaufmann:
Efficient Algorithms for Extreme Bandits. CoRR abs/2203.10883 (2022) - [i34]Clémence Réda
, Sattar Vakili, Emilie Kaufmann:
Near-Optimal Collaborative Learning in Bandits. CoRR abs/2206.00121 (2022) - [i33]Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide, Emilie Kaufmann:
Top Two Algorithms Revisited. CoRR abs/2206.05979 (2022) - [i32]Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann:
Optimistic PAC Reinforcement Learning: the Instance-Dependent View. CoRR abs/2207.05852 (2022) - [i31]Marc Jourdan, Rémy Degenne, Emilie Kaufmann:
Dealing with Unknown Variances in Best-Arm Identification. CoRR abs/2210.00974 (2022) - 2021
- [j5]Maryam Aziz, Emilie Kaufmann, Marie-Karelle Riviere:
On Multi-Armed Bandit Designs for Dose-Finding Trials. J. Mach. Learn. Res. 22: 14:1-14:38 (2021) - [j4]Emilie Kaufmann, Wouter M. Koolen:
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals. J. Mach. Learn. Res. 22: 246:1-246:44 (2021) - [c29]Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez:
Top-m identification for linear bandits. AISTATS 2021: 1108-1116 - [c28]Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko:
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces. AISTATS 2021: 3538-3546 - [c27]Omar Darwiche Domingues, Pierre Ménard, Emilie Kaufmann, Michal Valko:
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited. ALT 2021: 578-598 - [c26]Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko:
Adaptive Reward-Free Exploration. ALT 2021: 865-891 - [c25]Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric Maillard:
Optimal Thompson Sampling strategies for support-aware CVaR bandits. ICML 2021: 716-726 - [c24]Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko:
Kernel-Based Reinforcement Learning: A Finite-Time Analysis. ICML 2021: 2783-2792 - [c23]Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko:
Fast active learning for pure exploration in reinforcement learning. ICML 2021: 7599-7608 - [i30]Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez:
Top-m identification for linear bandits. CoRR abs/2103.10070 (2021) - 2020
- [c22]Abbas Mehrabian, Etienne Boursier, Emilie Kaufmann, Vianney Perchet:
A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players. AISTATS 2020: 1211-1221 - [c21]Xuedong Shang, Rianne de Heide, Pierre Ménard, Emilie Kaufmann, Michal Valko:
Fixed-confidence guarantees for Bayesian best-arm identification. AISTATS 2020: 1823-1832 - [c20]Cindy Trinh, Emilie Kaufmann, Claire Vernade, Richard Combes:
Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling. ALT 2020: 862-889 - [c19]Dorian Baudry, Emilie Kaufmann, Odalric-Ambrym Maillard:
Sub-sampling for Efficient Non-Parametric Bandit Exploration. NeurIPS 2020 - [c18]Anders Jonsson, Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Edouard Leurent, Michal Valko:
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity. NeurIPS 2020 - [i29]Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko:
Regret Bounds for Kernel-Based Reinforcement Learning. CoRR abs/2004.05599 (2020) - [i28]Anders Jonsson, Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Edouard Leurent, Michal Valko:
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity. CoRR abs/2006.05879 (2020) - [i27]Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko:
Adaptive Reward-Free Exploration. CoRR abs/2006.06294 (2020) - [i26]Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko:
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces. CoRR abs/2007.05078 (2020) - [i25]Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko:
Fast active learning for pure exploration in reinforcement learning. CoRR abs/2007.13442 (2020) - [i24]Omar Darwiche Domingues, Pierre Ménard, Emilie Kaufmann, Michal Valko:
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited. CoRR abs/2010.03531 (2020) - [i23]Dorian Baudry, Emilie Kaufmann, Odalric-Ambrym Maillard:
Sub-sampling for Efficient Non-Parametric Bandit Exploration. CoRR abs/2010.14323 (2020) - [i22]Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric-Ambrym Maillard:
Thompson Sampling for CVaR Bandits. CoRR abs/2012.05754 (2020)
2010 – 2019
- 2019
- [j3]Alexander Luedtke, Emilie Kaufmann, Antoine Chambaz:
Asymptotically optimal algorithms for budgeted multiple play bandits. Mach. Learn. 108(11): 1919-1949 (2019) - [c17]Xuedong Shang, Emilie Kaufmann, Michal Valko:
General parallel optimization a without metric. ALT 2019: 762-787 - [i21]Emilie Kaufmann, Abbas Mehrabian:
New Algorithms for Multiplayer Bandits when Arm Means Vary Among Players. CoRR abs/1902.01239 (2019) - [i20]Lilian Besson, Emilie Kaufmann:
The Generalized Likelihood Ratio Test meets klUCB: an Improved Algorithm for Piece-Wise Non-Stationary Bandits. CoRR abs/1902.01575 (2019) - [i19]Maryam Aziz, Emilie Kaufmann, Marie-Karelle Riviere:
On Multi-Armed Bandit Designs for Phase I Clinical Trials. CoRR abs/1903.07082 (2019) - [i18]Xuedong Shang, Rianne de Heide, Emilie Kaufmann, Pierre Ménard, Michal Valko:
Fixed-Confidence Guarantees for Bayesian Best-Arm Identification. CoRR abs/1910.10945 (2019) - [i17]Cindy Trinh, Emilie Kaufmann, Claire Vernade, Richard Combes:
Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling. CoRR abs/1912.03074 (2019) - 2018
- [j2]Emilie Kaufmann, Thomas Bonald, Marc Lelarge:
A spectral algorithm with additive clustering for the recovery of overlapping communities in networks. Theor. Comput. Sci. 742: 3-26 (2018) - [c16]Maryam Aziz, Jesse Anderton, Emilie Kaufmann, Javed A. Aslam:
Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence. ALT 2018: 3-24 - [c15]Lilian Besson, Emilie Kaufmann:
{Multi-Player Bandits Revisited}. ALT 2018: 56-92 - [c14]Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann:
Corrupt Bandits for Preserving Local Privacy. ALT 2018: 387-412 - [c13]Emilie Kaufmann, Wouter M. Koolen, Aurélien Garivier:
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling. NeurIPS 2018: 6335-6345 - [c12]Lilian Besson, Emilie Kaufmann, Christophe Moy:
Aggregation of multi-armed bandits learning algorithms for opportunistic spectrum access. WCNC 2018: 1-6 - [i16]Maryam Aziz, Jesse Anderton, Emilie Kaufmann, Javed A. Aslam:
Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence. CoRR abs/1803.04665 (2018) - [i15]Lilian Besson, Emilie Kaufmann:
What Doubling Tricks Can and Can't Do for Multi-Armed Bandits. CoRR abs/1803.06971 (2018) - [i14]Emilie Kaufmann, Wouter M. Koolen, Aurélien Garivier:
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling. CoRR abs/1806.00973 (2018) - [i13]Rémi Bonnefoi, Lilian Besson, Christophe Moy, Emilie Kaufmann, Jacques Palicot:
Multi-Armed Bandit Learning in IoT Networks: Learning helps even in non-stationary settings. CoRR abs/1807.00491 (2018) - [i12]Emilie Kaufmann, Wouter M. Koolen:
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals. CoRR abs/1811.11419 (2018) - 2017
- [c11]Rémi Bonnefoi, Lilian Besson, Christophe Moy, Emilie Kaufmann, Jacques Palicot:
Multi-Armed Bandit Learning in IoT Networks: Learning Helps Even in Non-stationary Settings. CrownCom 2017: 173-185 - [c10]Emilie Kaufmann, Wouter M. Koolen:
Monte-Carlo Tree Search by Best Arm Identification. NIPS 2017: 4897-4906 - [i11]Emilie Kaufmann, Aurélien Garivier:
Learning the distribution with largest mean: two bandit frameworks. CoRR abs/1702.00001 (2017) - [i10]Emilie Kaufmann, Wouter M. Koolen:
Monte-Carlo Tree Search by Best Arm Identification. CoRR abs/1706.02986 (2017) - [i9]Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann:
Corrupt Bandits for Privacy Preserving Input. CoRR abs/1708.05033 (2017) - [i8]Lilian Besson, Emilie Kaufmann:
Multi-Player Bandits Models Revisited. CoRR abs/1711.02317 (2017) - 2016
- [j1]Emilie Kaufmann, Olivier Cappé, Aurélien Garivier:
On the Complexity of Best-Arm Identification in Multi-Armed Bandit Models. J. Mach. Learn. Res. 17: 1:1-1:42 (2016) - [c9]Emilie Kaufmann, Thomas Bonald, Marc Lelarge:
A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks. ALT 2016: 355-370 - [c8]Aurélien Garivier, Emilie Kaufmann:
Optimal Best Arm Identification with Fixed Confidence. COLT 2016: 998-1027 - [c7]Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen:
Maximin Action Identification: A New Bandit Framework for Games. COLT 2016: 1028-1050 - [c6]Aurélien Garivier, Tor Lattimore, Emilie Kaufmann:
On Explore-Then-Commit strategies. NIPS 2016: 784-792 - [i7]Aurélien Garivier, Emilie Kaufmann:
Optimal Best Arm Identification with Fixed Confidence. CoRR abs/1602.04589 (2016) - [i6]Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen:
Maximin Action Identification: A New Bandit Framework for Games. CoRR abs/1602.04676 (2016) - [i5]Aurélien Garivier, Emilie Kaufmann, Tor Lattimore:
On Explore-Then-Commit Strategies. CoRR abs/1605.08988 (2016) - [i4]Alexander Luedtke, Emilie Kaufmann, Antoine Chambaz:
Asymptotically Optimal Algorithms for Multiple Play Bandits with Partial Feedback. CoRR abs/1606.09388 (2016) - 2014
- [b1]Emilie Kaufmann:
Analysis of bayesian and frequentist strategies for sequential resource allocation. (Analyse de stratégies bayésiennes et fréquentistes pour l'allocation séquentielle de ressources). Télécom ParisTech, France, 2014 - [c5]Emilie Kaufmann, Olivier Cappé, Aurélien Garivier:
On the Complexity of A/B Testing. COLT 2014: 461-481 - [i3]Emilie Kaufmann, Olivier Cappé, Aurélien Garivier:
On the Complexity of A/B Testing. CoRR abs/1405.3224 (2014) - [i2]Emilie Kaufmann, Olivier Cappé, Aurélien Garivier:
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models. CoRR abs/1407.4443 (2014) - 2013
- [c4]Emilie Kaufmann, Shivaram Kalyanakrishnan:
Information Complexity in Bandit Subset Selection. COLT 2013: 228-251 - [c3]Nathaniel Korda, Emilie Kaufmann, Rémi Munos:
Thompson Sampling for 1-Dimensional Exponential Family Bandits. NIPS 2013: 1448-1456 - 2012
- [c2]Emilie Kaufmann, Nathaniel Korda, Rémi Munos:
Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis. ALT 2012: 199-213 - [c1]Emilie Kaufmann, Olivier Cappé, Aurélien Garivier:
On Bayesian Upper Confidence Bounds for Bandit Problems. AISTATS 2012: 592-600 - [i1]Emilie Kaufmann, Nathaniel Korda, Rémi Munos:
Thompson Sampling: An Optimal Finite Time Analysis. CoRR abs/1205.4217 (2012)
Coauthor Index
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