2 citations · 4 across the 10 of their papers we have counts for
6 papers · 1 filter
Optimal Best Arm Identification under Differential Privacy
Marc Jourdan, Achraf Azize
Best Arm Identification (BAI) algorithms are deployed in data-sensitive applications, such as adaptive clinical trials or user studies. Driven by the privacy concerns of these appl…
Optimal Regret of Bernoulli Bandits under Global Differential Privacy
Achraf Azize, Yulian Wu, Junya Honda +3
As sequential learning algorithms are increasingly applied to real life, ensuring data privacy while maintaining their utilities emerges as a timely question. In this context, regr…
Differentially Private Best-Arm Identification
Achraf Azize, Marc Jourdan, Aymen Al Marjani +1
Best Arm Identification (BAI) problems are progressively used for data-sensitive applications, such as designing adaptive clinical trials, tuning hyper-parameters, and conducting u…
Conservative Exploration for Policy Optimization via Off-Policy Policy Evaluation
Paul Daoudi, Mathias Formoso, Othman Gaizi +2
A precondition for the deployment of a Reinforcement Learning agent to a real-world system is to provide guarantees on the learning process. While a learning algorithm will eventua…
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence
Achraf Azize, Marc Jourdan, Aymen Al Marjani +1
Best Arm Identification (BAI) problems are progressively used for data-sensitive applications, such as designing adaptive clinical trials, tuning hyper-parameters, and conducting u…
Concentrated Differential Privacy for Bandits
Achraf Azize, Debabrota Basu
Bandits serve as the theoretical foundation of sequential learning and an algorithmic foundation of modern recommender systems. However, recommender systems often rely on user-sens…