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Evrard Garcelon
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2020 – today
- 2023
- [c11]Cathy Yuanchen Li
, Jana Sotáková
, Emily Wenger
, Mohamed Malhou
, Evrard Garcelon
, François Charton
, Kristin E. Lauter
:
SalsaPicante: A Machine Learning Attack on LWE with Binary Secrets. CCS 2023: 2606-2620 - [i14]Cathy Yuanchen Li, Jana Sotáková, Emily Wenger, Mohamed Malhou, Evrard Garcelon, François Charton, Kristin E. Lauter:
SALSA PICANTE: a machine learning attack on LWE with binary secrets. CoRR abs/2303.04178 (2023) - [i13]Paul Daoudi, Mathias Formoso, Othman Gaizi, Achraf Azize, Evrard Garcelon:
Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation. CoRR abs/2312.15458 (2023) - [i12]Cathy Yuanchen Li, Jana Sotáková, Emily Wenger, Mohamed Malhou, Evrard Garcelon, François Charton, Kristin E. Lauter:
SALSA PICANTE: a machine learning attack on LWE with binary secrets. IACR Cryptol. ePrint Arch. 2023: 340 (2023) - 2022
- [c10]Evrard Garcelon, Matteo Pirotta, Vianney Perchet:
Encrypted Linear Contextual Bandit. AISTATS 2022: 2519-2551 - [c9]Evrard Garcelon, Vashist Avadhanula, Alessandro Lazaric, Matteo Pirotta:
Top K Ranking for Multi-Armed Bandit with Noisy Evaluations. AISTATS 2022: 6242-6269 - [c8]Evrard Garcelon, Kamalika Chaudhuri, Vianney Perchet, Matteo Pirotta:
Privacy Amplification via Shuffling for Linear Contextual Bandits. ALT 2022: 381-407 - [c7]Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon Shaolei Du:
A Reduction-Based Framework for Conservative Bandits and Reinforcement Learning. ICLR 2022 - 2021
- [c6]Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta:
Local Differential Privacy for Regret Minimization in Reinforcement Learning. NeurIPS 2021: 10561-10573 - [i11]Evrard Garcelon, Vianney Perchet, Matteo Pirotta:
Homomorphically Encrypted Linear Contextual Bandit. CoRR abs/2103.09927 (2021) - [i10]Yunchang Yang, Tianhao Wu, Han Zhong, Evrard Garcelon, Matteo Pirotta, Alessandro Lazaric, Liwei Wang, Simon S. Du:
A Unified Framework for Conservative Exploration. CoRR abs/2106.11692 (2021) - [i9]Paul Luyo, Evrard Garcelon, Alessandro Lazaric, Matteo Pirotta:
Differentially Private Exploration in Reinforcement Learning with Linear Representation. CoRR abs/2112.01585 (2021) - [i8]Evrard Garcelon, Kamalika Chaudhuri, Vianney Perchet, Matteo Pirotta:
Privacy Amplification via Shuffling for Linear Contextual Bandits. CoRR abs/2112.06008 (2021) - [i7]Evrard Garcelon, Vashist Avadhanula, Alessandro Lazaric, Matteo Pirotta:
Top K Ranking for Multi-Armed Bandit with Noisy Evaluations. CoRR abs/2112.06517 (2021) - 2020
- [c5]Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta:
Improved Algorithms for Conservative Exploration in Bandits. AAAI 2020: 3962-3969 - [c4]Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta:
Conservative Exploration in Reinforcement Learning. AISTATS 2020: 1431-1441 - [c3]Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric:
No-Regret Exploration in Goal-Oriented Reinforcement Learning. ICML 2020: 9428-9437 - [c2]Evrard Garcelon, Baptiste Rozière, Laurent Meunier, Jean Tarbouriech, Olivier Teytaud, Alessandro Lazaric, Matteo Pirotta:
Adversarial Attacks on Linear Contextual Bandits. NeurIPS 2020 - [i6]Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta:
Conservative Exploration in Reinforcement Learning. CoRR abs/2002.03218 (2020) - [i5]Evrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta:
Improved Algorithms for Conservative Exploration in Bandits. CoRR abs/2002.03221 (2020) - [i4]Evrard Garcelon, Baptiste Rozière, Laurent Meunier, Jean Tarbouriech, Olivier Teytaud, Alessandro Lazaric, Matteo Pirotta:
Adversarial Attacks on Linear Contextual Bandits. CoRR abs/2002.03839 (2020) - [i3]Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta:
Local Differentially Private Regret Minimization in Reinforcement Learning. CoRR abs/2010.07778 (2020)
2010 – 2019
- 2019
- [i2]Jean Tarbouriech, Evrard Garcelon, Michal Valko, Matteo Pirotta, Alessandro Lazaric:
No-Regret Exploration in Goal-Oriented Reinforcement Learning. CoRR abs/1912.03517 (2019) - 2018
- [c1]Rémy Degenne, Evrard Garcelon, Vianney Perchet:
Bandits with Side Observations: Bounded vs. Logarithmic Regret. UAI 2018: 467-476 - [i1]Rémy Degenne, Evrard Garcelon, Vianney Perchet:
Bandits with Side Observations: Bounded vs. Logarithmic Regret. CoRR abs/1807.03558 (2018)
Coauthor Index

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