Maxime Sangnier

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 13

Top Venues

CoRR

Mach. Learn.

AISTATS

MLSP

University of Rouen, France (PHD)

Education History

University of Rouen, France

PHD

Publications

Anna Bonnet, Miguel Martinez Herrera, Maxime Sangnier
Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity. Stat. Comput. 33 (4) (2023)
Erwan Fouillen, Claire Boyer, Maxime Sangnier
Proximal boosting: Aggregating weak learners to minimize non-differentiable losses. Neurocomputing 520 (2023)
Gérard Biau, Maxime Sangnier, Ugo Tanielian
Some Theoretical Insights into Wasserstein GANs. J. Mach. Learn. Res. 22 (2021)
Gérard Biau, Maxime Sangnier, Ugo Tanielian
Some Theoretical Insights into Wasserstein GANs. CoRR (2020)
Ugo Tanielian, Maxime Sangnier, Gérard Biau
Approximating Lipschitz continuous functions with GroupSort neural networks. CoRR (2020)
Romain Brault, Alex Lambert, Zoltán Szabó, Maxime Sangnier, Florence d'Alché-Buc
Infinite Task Learning in RKHSs. AISTATS (2019)
Gérard Biau, Benoît Cadre, Maxime Sangnier, Ugo Tanielian
Some Theoretical Properties of GANs. CoRR (2018)
Romain Brault, Alex Lambert, Zoltán Szabó, Maxime Sangnier, Florence d'Alché-Buc
Infinite-Task Learning with Vector-Valued RKHSs. CoRR (2018)
Moussab Djerrab, Alexandre Garcia, Maxime Sangnier, Florence d'Alché-Buc
Output Fisher embedding regression. Mach. Learn. 107 (8-10) (2018)
Erwan Fouillen, Claire Boyer, Maxime Sangnier
Accelerated proximal boosting. CoRR (2018)
Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc
Data sparse nonparametric regression with ε-insensitive losses. ACML (2017)
Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc
Joint quantile regression in vector-valued RKHSs. NIPS (2016)
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
Early and Reliable Event Detection Using Proximity Space Representation. ICML (2016)
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
Early frame-based detection of acoustic scenes. WASPAA (2015)
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
Filter bank learning for signal classification. Signal Process. 113 (2015)
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
Kernel learning as minimization of the single validation estimate. MLSP (2014)
Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy
Filter bank Kernel Learning for nonstationary signal classification. ICASSP (2013)

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Publication Activity (10 Years)

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Maxime Sangnier