Emilie Kaufmann

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 81

Top Venues

CoRR

ALT

NeurIPS

AISTATS

Télécom ParisTech, France (PHD)

Education History

Télécom ParisTech, France

PHD

Publications

Cyrille Kone, Emilie Kaufmann, Laura Richert
Bandit Pareto Set Identification: the Fixed Budget Setting. AISTATS (2024)
Tuan Dam, Odalric-Ambrym Maillard, Emilie Kaufmann
Power Mean Estimation in Stochastic Monte-Carlo Tree_Search. CoRR (2024)
Adrienne Tuynman, Rémy Degenne, Emilie Kaufmann
Finding good policies in average-reward Markov Decision Processes without prior knowledge. CoRR (2024)
Riccardo Poiani, Rémy Degenne, Emilie Kaufmann, Alberto Maria Metelli, Marcello Restelli
Optimal Multi-Fidelity Best-Arm Identification. CoRR (2024)
Marc Jourdan, Rémy Degenne, Emilie Kaufmann
An ε-Best-Arm Identification Algorithm for Fixed-Confidence and Beyond. NeurIPS (2023)
Marc Jourdan, Rémy Degenne, Emilie Kaufmann
Dealing with Unknown Variances in Best-Arm Identification. ALT (2023)
Cyrille Kone, Emilie Kaufmann, Laura Richert
Adaptive Algorithms for Relaxed Pareto Set Identification. NeurIPS (2023)
Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann
Active Coverage for PAC Reinforcement Learning. COLT (2023)
Marc Jourdan, Rémy Degenne, Emilie Kaufmann
An ε-Best-Arm Identification Algorithm for Fixed-Confidence and Beyond. CoRR (2023)
Cyrille Kone, Emilie Kaufmann, Laura Richert
Adaptive Algorithms for Relaxed Pareto Set Identification. CoRR (2023)
Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann
Optimistic PAC Reinforcement Learning: the Instance-Dependent View. ALT (2023)
Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann
Towards Instance-Optimality in Online PAC Reinforcement Learning. CoRR (2023)
Aymen Al Marjani, Andrea Tirinzoni, Emilie Kaufmann
Active Coverage for PAC Reinforcement Learning. CoRR (2023)
Cyrille Kone, Emilie Kaufmann, Laura Richert
Bandit Pareto Set Identification: the Fixed Budget Setting. CoRR (2023)
Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide, Emilie Kaufmann
Top Two Algorithms Revisited. CoRR (2022)
Dorian Baudry, Yoan Russac, Emilie Kaufmann
Efficient Algorithms for Extreme Bandits. AISTATS (2022)
Clémence Réda, Sattar Vakili, Emilie Kaufmann
Near-Optimal Collaborative Learning in Bandits. CoRR (2022)
Lilian Besson, Emilie Kaufmann, Odalric-Ambrym Maillard, Julien Seznec
Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits. J. Mach. Learn. Res. 23 (2022)
Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann
Optimistic PAC Reinforcement Learning: the Instance-Dependent View. CoRR (2022)
Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs. NeurIPS (2022)
Dorian Baudry, Yoan Russac, Emilie Kaufmann
Efficient Algorithms for Extreme Bandits. CoRR (2022)
Clémence Réda, Sattar Vakili, Emilie Kaufmann
Near-Optimal Collaborative Learning in Bandits. NeurIPS (2022)
Andrea Tirinzoni, Aymen Al Marjani, Emilie Kaufmann
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs. CoRR (2022)
Marc Jourdan, Rémy Degenne, Emilie Kaufmann
Dealing with Unknown Variances in Best-Arm Identification. CoRR (2022)
Marc Jourdan, Rémy Degenne, Dorian Baudry, Rianne de Heide, Emilie Kaufmann
Top Two Algorithms Revisited. NeurIPS (2022)
Maryam Aziz, Emilie Kaufmann, Marie-Karelle Riviere
On Multi-Armed Bandit Designs for Dose-Finding Trials. J. Mach. Learn. Res. 22 (2021)
Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez
Top-m identification for linear bandits. AISTATS (2021)
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)
Omar Darwiche Domingues, Pierre Ménard, Emilie Kaufmann, Michal Valko
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited. ALT (2021)
Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko
Adaptive Reward-Free Exploration. ALT (2021)
Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko
Fast active learning for pure exploration in reinforcement learning. ICML (2021)
Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez
Top-m identification for linear bandits. CoRR (2021)
Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko
Kernel-Based Reinforcement Learning: A Finite-Time Analysis. ICML (2021)
Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric Maillard
Optimal Thompson Sampling strategies for support-aware CVaR bandits. ICML (2021)
Emilie Kaufmann, Wouter M. Koolen
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals. J. Mach. Learn. Res. 22 (2021)
Dorian Baudry, Emilie Kaufmann, Odalric-Ambrym Maillard
Sub-sampling for Efficient Non-Parametric Bandit Exploration. NeurIPS (2020)
Abbas Mehrabian, Etienne Boursier, Emilie Kaufmann, Vianney Perchet
A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players. AISTATS (2020)
Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces. CoRR (2020)
Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric-Ambrym Maillard
Thompson Sampling for CVaR Bandits. CoRR (2020)
Cindy Trinh, Emilie Kaufmann, Claire Vernade, Richard Combes
Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling. ALT (2020)
Dorian Baudry, Emilie Kaufmann, Odalric-Ambrym Maillard
Sub-sampling for Efficient Non-Parametric Bandit Exploration. CoRR (2020)
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)
Omar Darwiche Domingues, Pierre Ménard, Emilie Kaufmann, Michal Valko
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited. CoRR (2020)
Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Emilie Kaufmann, Edouard Leurent, Michal Valko
Fast active learning for pure exploration in reinforcement learning. CoRR (2020)
Xuedong Shang, Rianne de Heide, Pierre Ménard, Emilie Kaufmann, Michal Valko
Fixed-confidence guarantees for Bayesian best-arm identification. AISTATS (2020)
Anders Jonsson, Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Edouard Leurent, Michal Valko
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity. CoRR (2020)
Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko
Adaptive Reward-Free Exploration. CoRR (2020)
Omar Darwiche Domingues, Pierre Ménard, Matteo Pirotta, Emilie Kaufmann, Michal Valko
Regret Bounds for Kernel-Based Reinforcement Learning. CoRR (2020)
Emilie Kaufmann, Abbas Mehrabian
New Algorithms for Multiplayer Bandits when Arm Means Vary Among Players. CoRR (2019)
Cindy Trinh, Emilie Kaufmann, Claire Vernade, Richard Combes
Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling. CoRR (2019)
Xuedong Shang, Emilie Kaufmann, Michal Valko
General parallel optimization a without metric. ALT (2019)
Alexander Luedtke, Emilie Kaufmann, Antoine Chambaz
Asymptotically optimal algorithms for budgeted multiple play bandits. Mach. Learn. 108 (11) (2019)
Lilian Besson, Emilie Kaufmann
The Generalized Likelihood Ratio Test meets klUCB: an Improved Algorithm for Piece-Wise Non-Stationary Bandits. CoRR (2019)
Maryam Aziz, Emilie Kaufmann, Marie-Karelle Riviere
On Multi-Armed Bandit Designs for Phase I Clinical Trials. CoRR (2019)
Xuedong Shang, Rianne de Heide, Emilie Kaufmann, Pierre Ménard, Michal Valko
Fixed-Confidence Guarantees for Bayesian Best-Arm Identification. CoRR (2019)
Lilian Besson, Emilie Kaufmann
What Doubling Tricks Can and Can't Do for Multi-Armed Bandits. CoRR (2018)
Emilie Kaufmann, Wouter M. Koolen, Aurélien Garivier
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling. CoRR (2018)
Emilie Kaufmann, Thomas Bonald, Marc Lelarge
A spectral algorithm with additive clustering for the recovery of overlapping communities in networks. Theor. Comput. Sci. 742 (2018)
Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann
Corrupt Bandits for Preserving Local Privacy. ALT (2018)
Maryam Aziz, Jesse Anderton, Emilie Kaufmann, Javed A. Aslam
Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence. CoRR (2018)
Emilie Kaufmann, Wouter M. Koolen
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals. CoRR (2018)
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 (2018)
Maryam Aziz, Jesse Anderton, Emilie Kaufmann, Javed A. Aslam
Pure Exploration in Infinitely-Armed Bandit Models with Fixed-Confidence. ALT (2018)
Lilian Besson, Emilie Kaufmann, Christophe Moy
Aggregation of multi-armed bandits learning algorithms for opportunistic spectrum access. WCNC (2018)
Emilie Kaufmann, Wouter M. Koolen, Aurélien Garivier
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling. NeurIPS (2018)
Lilian Besson, Emilie Kaufmann
{Multi-Player Bandits Revisited}. ALT (2018)
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)
Emilie Kaufmann, Wouter M. Koolen
Monte-Carlo Tree Search by Best Arm Identification. NIPS (2017)
Emilie Kaufmann, Wouter M. Koolen
Monte-Carlo Tree Search by Best Arm Identification. CoRR (2017)
Emilie Kaufmann, Aurélien Garivier
Learning the distribution with largest mean: two bandit frameworks. CoRR (2017)
Lilian Besson, Emilie Kaufmann
Multi-Player Bandits Models Revisited. CoRR (2017)
Pratik Gajane, Tanguy Urvoy, Emilie Kaufmann
Corrupt Bandits for Privacy Preserving Input. CoRR (2017)
Emilie Kaufmann, Olivier Cappé, Aurélien Garivier
On the Complexity of Best-Arm Identification in Multi-Armed Bandit Models. J. Mach. Learn. Res. 17 (2016)
Aurélien Garivier, Tor Lattimore, Emilie Kaufmann
On Explore-Then-Commit strategies. NIPS (2016)
Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen
Maximin Action Identification: A New Bandit Framework for Games. COLT (2016)
Alexander Luedtke, Emilie Kaufmann, Antoine Chambaz
Asymptotically Optimal Algorithms for Multiple Play Bandits with Partial Feedback. CoRR (2016)
Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen
Maximin Action Identification: A New Bandit Framework for Games. CoRR (2016)
Aurélien Garivier, Emilie Kaufmann, Tor Lattimore
On Explore-Then-Commit Strategies. CoRR (2016)
Emilie Kaufmann, Thomas Bonald, Marc Lelarge
A Spectral Algorithm with Additive Clustering for the Recovery of Overlapping Communities in Networks. ALT (2016)
Aurélien Garivier, Emilie Kaufmann
Optimal Best Arm Identification with Fixed Confidence. COLT (2016)
Aurélien Garivier, Emilie Kaufmann
Optimal Best Arm Identification with Fixed Confidence. CoRR (2016)
Emilie Kaufmann, Olivier Cappé, Aurélien Garivier
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models. CoRR (2014)
Emilie Kaufmann, Olivier Cappé, Aurélien Garivier
On the Complexity of A/B Testing. COLT (2014)
Emilie Kaufmann, Olivier Cappé, Aurélien Garivier
On the Complexity of A/B Testing. CoRR (2014)
Emilie Kaufmann, Shivaram Kalyanakrishnan
Information Complexity in Bandit Subset Selection. COLT (2013)
Nathaniel Korda, Emilie Kaufmann, Rémi Munos
Thompson Sampling for 1-Dimensional Exponential Family Bandits. NIPS (2013)
Emilie Kaufmann, Nathaniel Korda, Rémi Munos
Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis. ALT (2012)
Emilie Kaufmann, Olivier Cappé, Aurélien Garivier
On Bayesian Upper Confidence Bounds for Bandit Problems. AISTATS (2012)
Emilie Kaufmann, Nathaniel Korda, Rémi Munos
Thompson Sampling: An Optimal Finite Time Analysis CoRR (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Emilie Kaufmann