Adaptive and Optimal Online Linear Regression on ℓ1-Balls. - Sébastien Gerchinovitz; Jia Yuan Yu (ALT, 2011)

Sparsity regret bounds for individual sequences in online linear regression. - Sébastien Gerchinovitz (J. Mach. Learn. Res., 2013)

Adaptive and optimal online linear regression on l1-balls. - Sébastien Gerchinovitz; Jia Yuan Yu (Theor. Comput. Sci., 2014)

A Chaining Algorithm for Online Nonparametric Regression. - Pierre Gaillard; Sébastien Gerchinovitz (COLT, 2015)

A Multiple-Play Bandit Algorithm Applied to Recommender Systems. - Jonathan Louëdec; Max Chevalier; Josiane Mothe; Aurélien Garivier; Sébastien Gerchinovitz (FLAIRS, 2015)

Adaptive Simulated Annealing with Homogenization for Aircraft Trajectory Optimization. - Clément Bouttier; Olivier Babando; Sébastien Gadat; Sébastien Gerchinovitz; Serge Laporte; Florence Nicol (OR, 2015)

Refined Lower Bounds for Adversarial Bandits. - Sébastien Gerchinovitz; Tor Lattimore (NIPS, 2016)

Algorithmic Chaining and the Role of Partial Feedback in Online Nonparametric Learning. - Nicolò Cesa-Bianchi; Pierre Gaillard; Claudio Gentile; Sébastien Gerchinovitz (COLT, 2017)

Online Nonparametric Learning, Chaining, and the Role of Partial Feedback. - Nicolò Cesa-Bianchi; Pierre Gaillard; Claudio Gentile; Sébastien Gerchinovitz (CoRR, 2017)

Fano's inequality for random variables. - Sébastien Gerchinovitz; Pierre Ménard; Gilles Stoltz (CoRR, 2017)

Optimization of a SSP's Header Bidding Strategy using Thompson Sampling. - Grégoire Jauvion; Nicolas Grislain; Pascal Dkengne Sielenou; Aurélien Garivier; Sébastien Gerchinovitz (KDD, 2018)

Uniform regret bounds over Rd for the sequential linear regression problem with the square loss. - Pierre Gaillard; Sébastien Gerchinovitz; Malo Huard; Gilles Stoltz (ALT, 2019)

A High Probability Safety Guarantee for Shifted Neural Network Surrogates. - Melanie Ducoffe; Sébastien Gerchinovitz; Jayant Sen Gupta (SafeAI@AAAI, 2020)

Regret analysis of the Piyavskii-Shubert algorithm for global Lipschitz optimization. - Clément Bouttier; Tommaso Cesari; Sébastien Gerchinovitz (CoRR, 2020)

The Sample Complexity of Level Set Approximation. - François Bachoc; Tommaso Cesari; Sébastien Gerchinovitz (AISTATS, 2021)

Instance-Dependent Bounds for Zeroth-order Lipschitz Optimization with Error Certificates. - François Bachoc; Tommaso Cesari; Sébastien Gerchinovitz (NeurIPS, 2021)

Numerical influence of ReLU'(0) on backpropagation. - David Bertoin; Jérôme Bolte; Sébastien Gerchinovitz; Edouard Pauwels (NeurIPS, 2021)

Online nonparametric regression with Sobolev kernels. - Oleksandr Zadorozhnyi; Pierre Gaillard; Sébastien Gerchinovitz; Alessandro Rudi (CoRR, 2021)

White Paper Machine Learning in Certified Systems. - Hervé Delseny; Christophe Gabreau; Adrien Gauffriau; Bernard Beaudouin; Ludovic Ponsolle; Lucian Alecu; Hugues Bonnin; Brice Beltran; Didier Duchel; Jean-Brice Ginestet; Alexandre Hervieu; Ghilaine Martinez; et al. (CoRR, 2021)

A general approximation lower bound in $L^p$ norm, with applications to feed-forward neural networks. - El Mehdi Achour; Armand Foucault; Sébastien Gerchinovitz; François Malgouyres (NeurIPS, 2022)

Object Detection with Probabilistic Guarantees: A Conformal Prediction Approach. - Florence de Grancey; Jean-Luc Adam; Lucian Alecu; Sébastien Gerchinovitz; Franck Mamalet; David Vigouroux (SAFECOMP Workshops, 2022)

A general approximation lower bound in Lp norm, with applications to feed-forward neural networks. - El Mehdi Achour; Armand Foucault; Sébastien Gerchinovitz; François Malgouyres (CoRR, 2022)

Certified Multi-Fidelity Zeroth-Order Optimization. - Étienne de Montbrun; Sébastien Gerchinovitz (CoRR, 2023)

Adaptive approximation of monotone functions. - Pierre Gaillard; Sébastien Gerchinovitz; Étienne de Montbrun (CoRR, 2023)

The Loss Landscape of Deep Linear Neural Networks: a Second-order Analysis. - El Mehdi Achour; François Malgouyres; Sébastien Gerchinovitz (J. Mach. Learn. Res., 2024)

Certified Multifidelity Zeroth-Order Optimization. - Étienne de Montbrun; Sébastien Gerchinovitz (SIAM/ASA J. Uncertain. Quantification, 2024)

Diversity-Preserving K-Armed Bandits, Revisited. - Hédi Hadiji; Sébastien Gerchinovitz; Jean-Michel Loubes; Gilles Stoltz (Trans. Mach. Learn. Res., 2024)

Conformal Object Detection by Sequential Risk Control. - Léo Andéol; Luca Mossina; Adrien Mazoyer; Sébastien Gerchinovitz (CoRR, 2025)

Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks. - Thomas Massena; Léo Andéol; Thibaut Boissin; Franck Mamalet; Corentin Friedrich; Mathieu Serrurier; Sébastien Gerchinovitz (CoRR, 2025)