| 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 2nd IEEE Conference on Secure and Trustworthy Machine Learning, 0 | 2* | |
| 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 |
Debabrota BasuFaculty, Inria at University of Lille and CNRS (CRIStAL)Verified email at comp.nus.edu.sg
