Rover Descent: Learning to Optimize by Learning to Navigate on Prototypical Loss Surfaces. - Louis Faury; Flavian Vasile (LION, 2018)

Neural Generative Models for Global Optimization with Gradients. - Louis Faury; Flavian Vasile; Clément Calauzènes; Olivier Fercoq (CoRR, 2018)

Benchmarking GNN-CMA-ES on the BBOB noiseless testbed. - Louis Faury; Clément Calauzènes; Olivier Fercoq (GECCO (Companion), 2019)

Improving Evolutionary Strategies with Generative Neural Networks. - Louis Faury; Clément Calauzènes; Olivier Fercoq; Syrine Krichene (CoRR, 2019)

Distributionally Robust Counterfactual Risk Minimization. - Louis Faury; Ugo Tanielian; Elvis Dohmatob; Elena Smirnova; Flavian Vasile (AAAI, 2020)

Improved Optimistic Algorithms for Logistic Bandits. - Louis Faury; Marc Abeille; Clément Calauzènes; Olivier Fercoq (ICML, 2020)

Improving Offline Contextual Bandits with Distributional Robustness. - Otmane Sakhi; Louis Faury; Flavian Vasile (CoRR, 2020)

Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits. - Marc Abeille; Louis Faury; Clément Calauzènes (AISTATS, 2021)

Self-Concordant Analysis of Generalized Linear Bandits with Forgetting. - Yoan Russac; Louis Faury; Olivier Cappé; Aurélien Garivier (AISTATS, 2021)

A Technical Note on Non-Stationary Parametric Bandits: Existing Mistakes and Preliminary Solutions. - Louis Faury; Yoan Russac; Marc Abeille; Clément Calauzènes (ALT, 2021)

Regret Bounds for Generalized Linear Bandits under Parameter Drift. - Louis Faury; Yoan Russac; Marc Abeille; Clément Calauzènes (CoRR, 2021)

Variance-sensitive confidence intervals for parametric and offline bandits. (Intervalles de confiance sensibles à la variance : Applications aux bandits paramétriques et bandits hors ligne). - Louis Faury (2021)

Jointly Efficient and Optimal Algorithms for Logistic Bandits. - Louis Faury; Marc Abeille; Kwang-Sung Jun; Clément Calauzènes (AISTATS, 2022)