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Books and Theses
- 2015
[b1]Maxime Sangnier:
Outils d'apprentissage automatique pour la reconnaissance de signaux temporels. (Automatic learning tools for time signal recognition). University of Rouen, France, 2015
Journal Articles
- 2023
- [j5]Erwan Fouillen, Claire Boyer, Maxime Sangnier:
Proximal boosting: Aggregating weak learners to minimize non-differentiable losses. Neurocomputing 520: 301-319 (2023) - [j4]Anna Bonnet, Miguel Martinez Herrera
, Maxime Sangnier:
Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity. Stat. Comput. 33(4): 91 (2023) - 2021
- [j3]Gérard Biau, Maxime Sangnier, Ugo Tanielian:
Some Theoretical Insights into Wasserstein GANs. J. Mach. Learn. Res. 22: 119:1-119:45 (2021) - 2018
- [j2]Moussab Djerrab, Alexandre Garcia, Maxime Sangnier, Florence d'Alché-Buc:
Output Fisher embedding regression. Mach. Learn. 107(8-10): 1229-1256 (2018) - 2015
- [j1]Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy:
Filter bank learning for signal classification. Signal Process. 113: 124-137 (2015)
Conference and Workshop Papers
- 2019
- [c7]Romain Brault, Alex Lambert, Zoltán Szabó, Maxime Sangnier, Florence d'Alché-Buc:
Infinite Task Learning in RKHSs. AISTATS 2019: 1294-1302 - 2017
- [c6]Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc:
Data sparse nonparametric regression with ε-insensitive losses. ACML 2017: 192-207 - 2016
- [c5]Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy:
Early and Reliable Event Detection Using Proximity Space Representation. ICML 2016: 2310-2319 - [c4]Maxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc:
Joint quantile regression in vector-valued RKHSs. NIPS 2016: 3693-3701 - 2015
- [c3]Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy:
Early frame-based detection of acoustic scenes. WASPAA 2015: 1-5 - 2014
- [c2]Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy:
Kernel learning as minimization of the single validation estimate. MLSP 2014: 1-6 - 2013
- [c1]Maxime Sangnier, Jérôme Gauthier, Alain Rakotomamonjy:
Filter bank Kernel Learning for nonstationary signal classification. ICASSP 2013: 3183-3187
Informal and Other Publications
- 2020
- [i5]Gérard Biau, Maxime Sangnier, Ugo Tanielian:
Some Theoretical Insights into Wasserstein GANs. CoRR abs/2006.02682 (2020) - [i4]Ugo Tanielian, Maxime Sangnier, Gérard Biau:
Approximating Lipschitz continuous functions with GroupSort neural networks. CoRR abs/2006.05254 (2020) - 2018
- [i3]Gérard Biau, Benoît Cadre, Maxime Sangnier, Ugo Tanielian:
Some Theoretical Properties of GANs. CoRR abs/1803.07819 (2018) - [i2]Romain Brault, Alex Lambert, Zoltán Szabó, Maxime Sangnier, Florence d'Alché-Buc:
Infinite-Task Learning with Vector-Valued RKHSs. CoRR abs/1805.08809 (2018) - [i1]Erwan Fouillen, Claire Boyer, Maxime Sangnier:
Accelerated proximal boosting. CoRR abs/1808.09670 (2018)
Coauthor Index
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