193 citations
- Université de LilleFR199 papers
- Centre National de la Recherche ScientifiqueFR190 papers
- Centre de Recherche en Informatique, Signal et Automatique de LilleFR140 papers
- Université Paris-SaclayFR62 papers
- Centre de Recherche en InformatiqueFR57 papers
- Institut d'Astrophysique SpatialeFR56 papers
- Sorbonne UniversitéFR56 papers
- Université Paris CitéFR55 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR52 papers
- Université Grenoble AlpesFR51 papers
- CEA Paris-SaclayFR50 papers
- Institut de Recherche en Astrophysique et PlanétologieFR50 papers
10 papers · 1 filter
DP-SPRT: Differentially Private Sequential Probability Ratio Tests
Thomas Michel, Debabrota Basu, Emilie Kaufmann
We revisit Wald's celebrated Sequential Probability Ratio Test for sequential tests of two simple hypotheses, under privacy constraints. We propose DP-SPRT, a wrapper that can be c…
Adaptive collaboration for online personalized distributed learning with heterogeneous clients
Constantin Philippenko, Batiste Le Bars, Kevin Scaman +1
We study the problem of online personalized decentralized learning with statistically heterogeneous clients collaborating to accelerate local training. An important challenge i…
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…
FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear Bandits
Sunrit Chakraborty, Saptarshi Roy, Debabrota Basu
High dimensional sparse linear bandits serve as an efficient model for sequential decision-making problems (e.g. personalized medicine), where high dimensional features (e.g. genom…
Signal reconstruction using determinantal sampling
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
We study the approximation of a square-integrable function from a finite number of evaluations on a random set of nodes according to a well-chosen distribution. This is particularl…
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption
Shubhada Agrawal, Timothée Mathieu, Debabrota Basu +1
We investigate the regret-minimisation problem in a multi-armed bandit setting with arbitrary corruptions. Similar to the classical setup, the agent receives rewards generated inde…