Maxime Sangnier

According to our database, Maxime Sangnier authored at least 17 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity.

Anna Bonnet, Miguel Martinez Herrera, Maxime Sangnier

Stat. Comput., August, 2023

Proximal boosting: Aggregating weak learners to minimize non-differentiable losses.

Erwan Fouillen, Claire Boyer, Maxime Sangnier

Neurocomputing, 2023

2021

Some Theoretical Insights into Wasserstein GANs.

Gérard Biau, Maxime Sangnier, Ugo Tanielian

J. Mach. Learn. Res., 2021

2020

Approximating Lipschitz continuous functions with GroupSort neural networks.

Ugo Tanielian, Maxime Sangnier, Gérard Biau

CoRR, 2020

2019

Infinite Task Learning in RKHSs.

Romain Brault, Alex Lambert, Zoltán Szabó, Maxime Sangnier, Florence d'Alché-Buc

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Output Fisher embedding regression.

Moussab Djerrab, Alexandre Garcia, Maxime Sangnier, Florence d'Alché-Buc

Mach. Learn., 2018

Accelerated proximal boosting.

Erwan Fouillen, Claire Boyer, Maxime Sangnier

CoRR, 2018

Infinite-Task Learning with Vector-Valued RKHSs.

Romain Brault, Alex Lambert, Zoltán Szabó, Maxime Sangnier, Florence d'Alché-Buc

CoRR, 2018

Some Theoretical Properties of GANs.

Gérard Biau, Benoît Cadre, Maxime Sangnier, Ugo Tanielian

CoRR, 2018

2017

Data sparse nonparametric regression with ε-insensitive losses.

Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc

Proceedings of The 9th Asian Conference on Machine Learning, 2017

2016

Joint quantile regression in vector-valued RKHSs.

Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Early and Reliable Event Detection Using Proximity Space Representation.

Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

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

Maxime Sangnier

PhD thesis, 2015

Filter bank learning for signal classification.

Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy

Signal Process., 2015

Early frame-based detection of acoustic scenes.

Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy

Proceedings of the 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2015

2014

Kernel learning as minimization of the single validation estimate.

Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

2013

Filter bank Kernel Learning for nonstationary signal classification.

Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy

Proceedings of the IEEE International Conference on Acoustics, 2013