Pure Exploration and Regret Minimization in Matching Bandits. - Flore Sentenac; Jialin Yi; Clément Calauzènes; Vianney Perchet; Milan Vojnovic (ICML, 2021)

Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm. - Nathan Noiry; Vianney Perchet; Flore Sentenac (NeurIPS, 2021)

Decentralized Learning in Online Queuing Systems. - Flore Sentenac; Etienne Boursier; Vianney Perchet (NeurIPS, 2021)

Static Scheduling with Predictions Learned through Efficient Exploration. - Hugo Richard; Flore Sentenac; Corentin Odic; Mathieu Molina; Vianney Perchet (CoRR, 2022)

Robust Estimation of Discrete Distributions under Local Differential Privacy. - Julien Chhor; Flore Sentenac (ALT, 2023)

On Preemption and Learning in Stochastic Scheduling. - Nadav Merlis; Hugo Richard; Flore Sentenac; Corentin Odic; Mathieu Molina; Vianney Perchet (ICML, 2023)

Online Matching in Geometric Random Graphs. - Flore Sentenac; Nathan Noiry; Matthieu Lerasle; Laurent Ménard; Vianney Perchet (CoRR, 2023)

Almost Free: Self-concordance in Natural Exponential Families and an Application to Bandits. - Shuai Liu; Alex Ayoub; Flore Sentenac; Xiaoqi Tan; Csaba Szepesvári (NeurIPS, 2024)

Balancing optimism and pessimism in offline-to-online learning. - Flore Sentenac; Lee Albin; Csaba Szepesvári (CoRR, 2025)