Evrard Garcelon
Evrard Garcelon
Facebook AI Research
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Cited by
Cited by
No-Regret Exploration in Goal-Oriented Reinforcement Learning
J Tarbouriech, E Garcelon, M Valko, M Pirotta, A Lazaric
International Conference on Machine Learning 2020 (ICML2020), 2019
Improved Algorithms for Conservative Exploration in Bandits
E Garcelon, M Ghavamzadeh, A Lazaric, M Pirotta
AAAI2020, 2020
Conservative exploration in reinforcement learning
E Garcelon, M Ghavamzadeh, A Lazaric, M Pirotta
International Conference on Artificial Intelligence and Statistics 2020 …, 2020
Adversarial Attacks on Linear Contextual Bandits
E Garcelon, B Roziere, L Meunier, J Tarbouriech, O Teytaud, A Lazaric, ...
Advances in Neural Information Processing Systems 2020 (NeurIPS2020), 2020
Bandits with side observations: Bounded vs. logarithmic regret
R Degenne, E Garcelon, V Perchet
Uncertainty in Artificial Intelligence 2018 (UAI2018), 2018
Local differentially private regret minimization in reinforcement learning
E Garcelon, V Perchet, C Pike-Burke, M Pirotta
arXiv preprint arXiv:2010.07778, 2020
A Unified Framework for Conservative Exploration
Y Yang, T Wu, H Zhong, E Garcelon, M Pirotta, A Lazaric, L Wang, SS Du
arXiv preprint arXiv:2106.11692, 2021
Homomorphically Encrypted Linear Contextual Bandit
E Garcelon, V Perchet, M Pirotta
arXiv preprint arXiv:2103.09927, 2021
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