Nicolas P. Couellan

According to our database, Nicolas P. Couellan authored at least 25 papers between 1996 and 2024.

Collaborative distances:

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

2024

Theoretical aspects of robust SVM optimization in Banach spaces and Nash equilibrium interpretation.

Mohammed Sbihi, Nicolas Couellan

Ann. Math. Artif. Intell., October, 2024

A Time-Dependent Subgraph-Capacity Model for Multiple Shortest Paths and Application to CO₂/Contrail-Safe Aircraft Trajectories.

Céline Demouge, Marcel Mongeau, Nicolas Couellan, Daniel Delahaye

Oper. Res. Forum, September, 2024

Foreword.

Giancarlo Bigi, Sonia Cafieri, Nicolas Couëllan, Sophie Jan, Frédéric Messine

Optim. Methods Softw., 2024

Distributional loss for convolutional neural network regression and application to parameter estimation in satellite navigation signals.

Thomas Gonzalez, Antoine Blais, Nicolas Couëllan, Christian Ruiz

Expert Syst. Appl., 2024

Cartan moving frames and the data manifolds.

Eliot Tron, Rita Fioresi, Nicolas Couellan, Stéphane Puechmorel

CoRR, 2024

2023

LRP-GUS: A Visual Based Data Reduction Algorithm for Neural Networks.

Arnaud Guibert, Christophe Hurter, Nicolas Couellan

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

2022

Distributional loss for convolutional neural network regression and application to GNSS multi-path estimation.

Thomas Gonzalez, Antoine Blais, Nicolas Couëllan, Christian Ruiz

CoRR, 2022

Canonical foliations of neural networks: application to robustness.

Eliot Tron, Nicolas Couellan, Stéphane Puechmorel

CoRR, 2022

Robust SVM Optimization in Banach spaces.

Mohammed Sbihi, Nicolas Couellan

CoRR, 2022

A novel image representation of GNSS correlation for deep learning multipath detection.

Antoine Blais, Nicolas Couellan, Evgenii Munin

Array, 2022

2021

The Coupling Effect of Lipschitz Regularization in Neural Networks.

Nicolas P. Couellan

SN Comput. Sci., 2021

Probabilistic robustness estimates for feed-forward neural networks.

Nicolas P. Couellan

Neural Networks, 2021

2020

Feature uncertainty bounds for explicit feature maps and large robust nonlinear SVM classifiers.

Nicolas P. Couellan, Sophie Jan

Ann. Math. Artif. Intell., 2020

2019

Using Wasserstein-2 regularization to ensure fair decisions with Neural-Network classifiers.

Laurent Risser, Quentin Vincenot, Nicolas P. Couellan, Jean-Michel Loubes

CoRR, 2019

The coupling effect of Lipschitz regularization in deep neural networks.

Nicolas P. Couellan

CoRR, 2019

2017

A note on supervised classification and Nash-equilibrium problems.

Nicolas P. Couellan

RAIRO Oper. Res., 2017

Uncertainty-safe large scale support vector machines.

Nicolas P. Couellan, Wenjuan Wang

Comput. Stat. Data Anal., 2017

Feature uncertainty bounding schemes for large robust nonlinear SVM classifiers.

Nicolas P. Couellan, Sophie Jan

CoRR, 2017

2015

Bi-level stochastic gradient for large scale support vector machine.

Nicolas P. Couellan, Wenjuan Wang

Neurocomputing, 2015

Self-adaptive Support Vector Machine: A multi-agent optimization perspective.

Nicolas P. Couellan, Sophie Jan, Tom Jorquera, Jean-Pierre Georgé

Expert Syst. Appl., 2015

2014

Incremental accelerated gradient methods for SVM classification: study of the constrained approach.

Nicolas P. Couellan, Sophie Jan

Comput. Manag. Sci., 2014

2013

On-line SVM learning via an incremental primal-dual technique.

Nicolas P. Couellan, Theodore B. Trafalis

Optim. Methods Softw., 2013

An incremental primal-dual method for nonlinear programming with special structure.

Nicolas P. Couellan, Theodore B. Trafalis

Optim. Lett., 2013

1997

Training of supervised neural networks via a nonlinear primal-dual interior-point method.

Theodore B. Trafalis, Nicolas P. Couellan, Sébastien C. Bertrand

Proceedings of International Conference on Neural Networks (ICNN'97), 1997

1996

Neural network training via an affine scaling quadratic optimization algorithm.

Theodore B. Trafalis, Nicolas P. Couellan

Neural Networks, 1996