| When privacy meets partial information: A refined analysis of differentially private bandits A Azize, D Basu NeurIPS 2022, 2022 | 12 | 2022 |
| Concentrated Differential Privacy for Bandits A Azize, D Basu 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 78-109, 2024 | 2* | 2024 |
| On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence A Azize, M Jourdan, AA Marjani, D Basu NeurIPS 2023, 2023 | 1 | 2023 |
| How Much Does Each Datapoint Leak Your Privacy? Quantifying the Per-datum Membership Leakage A Azize, D Basu arXiv preprint arXiv:2402.10065, 2024 | | 2024 |
| Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation P Daoudi, M Formoso, O Gaizi, A Azize, E Garcelon arXiv preprint arXiv:2312.15458, 2023 | | 2023 |
| Rényi Differentially Private Bandits A Azize, D Basu AAAI Workshop on Privacy Preserving AI, 2023 | | 2023 |
| Conservative Optimistic Policy Optimization via Multiple Importance Sampling A Azize, O Gaizi arXiv preprint arXiv:2103.03307, 2021 | | 2021 |
| 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)| 979-8-3503-4950-4/24/$31.00© 2024 IEEE| DOI: 10.1109/SaTML59370. 2024.00043 U Aïvodji, G Anderson, R Anderson, S Aydore, A Azize, D Basu, ... | | |
Debabrota BasuFaculty, Inria at University of Lille and CNRS (CRIStAL)Verified email at comp.nus.edu.sg
