From Optimality to Robustness: Adaptive Re-Sampling Strategies in Stochastic Bandits. - Dorian Baudry; Patrick Saux; Odalric-Ambrym Maillard (NeurIPS, 2021)

From Optimality to Robustness: Dirichlet Sampling Strategies in Stochastic Bandits. - Dorian Baudry; Patrick Saux; Odalric-Ambrym Maillard (CoRR, 2021)

Risk-aware linear bandits with convex loss. - Patrick Saux; Odalric Maillard (AISTATS, 2023)

Bregman Deviations of Generic Exponential Families. - Sayak Ray Chowdhury; Patrick Saux; Odalric Maillard; Aditya Gopalan (COLT, 2023)

Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study. - Patrick Saux; Pierre Bauvin; Violeta Raverdy; Julien Teigny; Hélène Verkindt; Tomy Soumphonphakdy; Maxence Debert; Anne Jacobs 003; Daan Jacobs; Valerie Monpellier; Phong Ching Lee; Chin Hong Lim; et al. (CoRR, 2023)

Mathematics of statistical sequential decision-making: concentration, risk-awareness and modelling in stochastic bandits, with applications to bariatric surgery. - Patrick Saux (CoRR, 2024)

Mathematics of statistical sequential decision-making: concentration, risk-awareness and modelling in stochastic bandits, with applications to bariatric surgery. (Mathématiques de la prise de décision séquentielle statistique : concentration, aversion au risque et modélisation pour les bandits stochastiques, et applications à la chirurgie bariatrique). - Patrick Saux (2024)