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Nicolas P. Couellan
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2020 – today
- 2024
- [j16]Mohammed Sbihi, Nicolas Couellan:
Theoretical aspects of robust SVM optimization in Banach spaces and Nash equilibrium interpretation. Ann. Math. Artif. Intell. 92(5): 1273-1293 (2024) - [j15]Thomas Gonzalez, Antoine Blais
, Nicolas Couëllan
Distributional loss for convolutional neural network regression and application to parameter estimation in satellite navigation signals. Expert Syst. Appl. 255: 124682 (2024) - [j14]Giancarlo Bigi, Sonia Cafieri, Nicolas Couëllan, Sophie Jan, Frédéric Messine:
Foreword. Optim. Methods Softw. 39(1): 1-3 (2024) - [j13]Céline Demouge, Marcel Mongeau, Nicolas Couellan, Daniel Delahaye:
A Time-Dependent Subgraph-Capacity Model for Multiple Shortest Paths and Application to CO 2/Contrail-Safe Aircraft Trajectories. Oper. Res. Forum 5(3): 71 (2024) - [i7]Eliot Tron, Rita Fioresi, Nicolas Couellan, Stéphane Puechmorel:
Cartan moving frames and the data manifolds. CoRR abs/2409.12057 (2024) - 2023
- [c2]Arnaud Guibert
LRP-GUS: A Visual Based Data Reduction Algorithm for Neural Networks. ICANN (5) 2023: 337-349 - 2022
- [j12]Antoine Blais
A novel image representation of GNSS correlation for deep learning multipath detection. Array 14: 100167 (2022) - [i6]Mohammed Sbihi
Robust SVM Optimization in Banach spaces. CoRR abs/2202.08567 (2022) - [i5]Eliot Tron
Canonical foliations of neural networks: application to robustness. CoRR abs/2203.00922 (2022) - [i4]Thomas Gonzalez, Antoine Blais, Nicolas Couëllan, Christian Ruiz:
Distributional loss for convolutional neural network regression and application to GNSS multi-path estimation. CoRR abs/2206.01473 (2022) - 2021
- [j11]Nicolas P. Couellan
Probabilistic robustness estimates for feed-forward neural networks. Neural Networks 142: 138-147 (2021) - [j10]Nicolas P. Couellan
The Coupling Effect of Lipschitz Regularization in Neural Networks. SN Comput. Sci. 2(2): 113 (2021) - 2020
- [j9]Nicolas P. Couellan
Feature uncertainty bounds for explicit feature maps and large robust nonlinear SVM classifiers. Ann. Math. Artif. Intell. 88(1-3): 269-289 (2020)
2010 – 2019
- 2019
- [i3]Nicolas P. Couellan
The coupling effect of Lipschitz regularization in deep neural networks. CoRR abs/1904.06253 (2019) - [i2]Laurent Risser, Quentin Vincenot, Nicolas P. Couellan
Using Wasserstein-2 regularization to ensure fair decisions with Neural-Network classifiers. CoRR abs/1908.05783 (2019) - 2017
- [j8]Nicolas P. Couellan
Uncertainty-safe large scale support vector machines. Comput. Stat. Data Anal. 109: 215-230 (2017) - [j7]Nicolas P. Couellan
A note on supervised classification and Nash-equilibrium problems. RAIRO Oper. Res. 51(2): 329-341 (2017) - [i1]Nicolas P. Couellan, Sophie Jan:
Feature uncertainty bounding schemes for large robust nonlinear SVM classifiers. CoRR abs/1706.09795 (2017) - 2015
- [j6]Nicolas P. Couellan
Self-adaptive Support Vector Machine: A multi-agent optimization perspective. Expert Syst. Appl. 42(9): 4284-4298 (2015) - [j5]Nicolas P. Couellan
Bi-level stochastic gradient for large scale support vector machine. Neurocomputing 153: 300-308 (2015) - 2014
- [j4]Nicolas P. Couellan
Incremental accelerated gradient methods for SVM classification: study of the constrained approach. Comput. Manag. Sci. 11(4): 419-444 (2014) - 2013
- [j3]Nicolas P. Couellan
An incremental primal-dual method for nonlinear programming with special structure. Optim. Lett. 7(1): 51-62 (2013) - [j2]Nicolas P. Couellan
On-line SVM learning via an incremental primal-dual technique. Optim. Methods Softw. 28(2): 256-275 (2013)
1990 – 1999
- 1997
- [c1]Theodore B. Trafalis, Nicolas P. Couellan
Training of supervised neural networks via a nonlinear primal-dual interior-point method. ICNN 1997: 2017-2021 - 1996
- [j1]Theodore B. Trafalis
Neural network training via an affine scaling quadratic optimization algorithm. Neural Networks 9(3): 475-481 (1996)
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