Maxime Sangnier

20 papers A* 1A 2C 1Misc 1Journal 11Unranked 3
YearRankTypeTitle / Venue / Authors
2025 A conf
Nonparametric estimation of Hawkes processes with RKHSs.
AISTATS
Anna Bonnet, Maxime Sangnier
2024 J jnl
Nonparametric estimation of Hawkes processes with RKHSs.
CoRR
Anna Bonnet, Maxime Sangnier
2023 J jnl
Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity.
Stat. Comput.
Anna Bonnet, Miguel Martinez Herrera, Maxime Sangnier
2023 J jnl
Proximal boosting: Aggregating weak learners to minimize non-differentiable losses.
Neurocomputing
Erwan Fouillen, Claire Boyer, Maxime Sangnier
2021 J jnl
Some Theoretical Insights into Wasserstein GANs.
J. Mach. Learn. Res.
Gérard Biau, Maxime Sangnier, Ugo Tanielian
2020 J jnl
Approximating Lipschitz continuous functions with GroupSort neural networks.
CoRR
Ugo Tanielian, Maxime Sangnier, Gérard Biau
2020 J jnl
Some Theoretical Insights into Wasserstein GANs.
CoRR
Gérard Biau, Maxime Sangnier, Ugo Tanielian
2019 A conf
Infinite Task Learning in RKHSs.
AISTATS
Romain Brault, Alex Lambert, Zoltán Szabó, Maxime Sangnier, Florence d'Alché-Buc
2018 J jnl
Accelerated proximal boosting.
CoRR
Erwan Fouillen, Claire Boyer, Maxime Sangnier
2018 J jnl
Infinite-Task Learning with Vector-Valued RKHSs.
CoRR
Romain Brault, Alex Lambert, Zoltán Szabó, Maxime Sangnier, Florence d'Alché-Buc
2018 J jnl
Output Fisher embedding regression.
Mach. Learn.
Moussab Djerrab, Alexandre Garcia, Maxime Sangnier, Florence d'Alché-Buc
2018 J jnl
Some Theoretical Properties of GANs.
CoRR
Gérard Biau, Benoît Cadre, Maxime Sangnier, Ugo Tanielian
2017 C conf
Data sparse nonparametric regression with ε-insensitive losses.
ACML
Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc
2016 A* conf
Early and Reliable Event Detection Using Proximity Space Representation.
ICML
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
2016 — conf
Joint quantile regression in vector-valued RKHSs.
NIPS
Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc
2015 — conf
Early frame-based detection of acoustic scenes.
WASPAA
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
2015 J jnl
Filter bank learning for signal classification.
Signal Process.
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
2015 — —
Outils d'apprentissage automatique pour la reconnaissance de signaux temporels. (Automatic learning tools for time signal recognition).
Maxime Sangnier
2014 — conf
Kernel learning as minimization of the single validation estimate.
MLSP
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
2013 Misc conf
Filter bank Kernel Learning for nonstationary signal classification.
ICASSP
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy