Filter bank Kernel Learning for nonstationary signal classification. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (ICASSP, 2013)

Kernel learning as minimization of the single validation estimate. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (MLSP, 2014)

Early frame-based detection of acoustic scenes. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (WASPAA, 2015)

Filter bank learning for signal classification. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (Signal Process., 2015)

Outils d'apprentissage automatique pour la reconnaissance de signaux temporels. (Automatic learning tools for time signal recognition). - Maxime Sangnier (2015)

Early and Reliable Event Detection Using Proximity Space Representation. - Maxime Sangnier; Jérôme Gauthier; Alain Rakotomamonjy (ICML, 2016)

Joint quantile regression in vector-valued RKHSs. - Maxime Sangnier; Olivier Fercoq; Florence d'Alché-Buc (NIPS, 2016)

Data sparse nonparametric regression with ε-insensitive losses. - Maxime Sangnier; Olivier Fercoq; Florence d'Alché-Buc (ACML, 2017)

Some Theoretical Properties of GANs. - Gérard Biau; Benoît Cadre; Maxime Sangnier; Ugo Tanielian (CoRR, 2018)

Infinite-Task Learning with Vector-Valued RKHSs. - Romain Brault; Alex Lambert; Zoltán Szabó; Maxime Sangnier; Florence d'Alché-Buc (CoRR, 2018)

Accelerated proximal boosting. - Erwan Fouillen; Claire Boyer; Maxime Sangnier (CoRR, 2018)

Output Fisher embedding regression. - Moussab Djerrab; Alexandre Garcia 001; Maxime Sangnier; Florence d'Alché-Buc (Mach. Learn., 2018)

Infinite Task Learning in RKHSs. - Romain Brault; Alex Lambert; Zoltán Szabó; Maxime Sangnier; Florence d'Alché-Buc (AISTATS, 2019)

Approximating Lipschitz continuous functions with GroupSort neural networks. - Ugo Tanielian; Maxime Sangnier; Gérard Biau (CoRR, 2020)

Some Theoretical Insights into Wasserstein GANs. - Gérard Biau; Maxime Sangnier; Ugo Tanielian (J. Mach. Learn. Res., 2021)

Proximal boosting: Aggregating weak learners to minimize non-differentiable losses. - Erwan Fouillen; Claire Boyer; Maxime Sangnier (Neurocomputing, 2023)

Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity. - Anna Bonnet; Miguel Martinez Herrera; Maxime Sangnier (Stat. Comput., 2023)

Nonparametric estimation of Hawkes processes with RKHSs. - Anna Bonnet; Maxime Sangnier (AISTATS, 2025)