Conservative Optimistic Policy Optimization via Multiple Importance Sampling. - Achraf Azize; Othman Gaizi (CoRR, 2021)

When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits. - Achraf Azize; Debabrota Basu (NeurIPS, 2022)

On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence. - Achraf Azize; Marc Jourdan; Aymen Al Marjani; Debabrota Basu (NeurIPS, 2023)

Interactive and Concentrated Differential Privacy for Bandits. - Achraf Azize; Debabrota Basu (CoRR, 2023)

Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation. - Paul Daoudi; Mathias Formoso; Othman Gaizi; Achraf Azize; Evrard Garcelon (CoRR, 2023)

Open Problem: What is the Complexity of Joint Differential Privacy in Linear Contextual Bandits? - Achraf Azize; Debabrota Basu (COLT, 2024)

Concentrated Differential Privacy for Bandits. - Achraf Azize; Debabrota Basu (SaTML, 2024)

How Much Does Each Datapoint Leak Your Privacy? Quantifying the Per-datum Membership Leakage. - Achraf Azize; Debabrota Basu (CoRR, 2024)

Differentially Private Best-Arm Identification. - Achraf Azize; Marc Jourdan; Aymen Al Marjani; Debabrota Basu (CoRR, 2024)

Privacy-Utility Trade-offs in Sequential Decision-Making under Uncertainty. (Compromis entre confidentialité et utilité dans la prise de décision séquentielle dans l'incertain). - Achraf Azize (2024)

Some Targets Are Harder to Identify than Others: Quantifying the Target-dependent Membership Leakage. - Achraf Azize; Debabrota Basu (AISTATS, 2025)

Optimal Regret of Bernoulli Bandits under Global Differential Privacy. - Achraf Azize; Yulian Wu; Junya Honda; Francesco Orabona; Shinji Ito; Debabrota Basu (CoRR, 2025)