Simon Bernard

According to our database, Simon Bernard authored at least 25 papers between 2007 and 2024.

Collaborative distances:

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

2024

Random forest kernel for high-dimension low sample size classification.

Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal, Laurent Heutte

Stat. Comput., February, 2024

Pseudo-Labeling With Large Language Models for Multi-Label Emotion Classification of French Tweets.

Usman Malik, Simon Bernard, Alexandre Pauchet, Clément Chatelain, Romain Picot-Clémente, Jérôme Cortinovis

IEEE Access, 2024

2023

Random Forest Dissimilarity for High-Dimension Low Sample Size Classification.

Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal, Laurent Heutte

CoRR, 2023

Multiple Noises in Diffusion Model for Semi-Supervised Multi-Domain Translation.

Tsiry Mayet, Simon Bernard, Clément Chatelain, Romain Hérault

CoRR, 2023

Towards Long-Term predictions of Turbulence using Neural Operators.

Fernando Gonzalez, François-Xavier Demoulin, Simon Bernard

CoRR, 2023

Domain Translation via Latent Space Mapping.

Tsiry Mayet, Simon Bernard, Clément Chatelain, Romain Hérault

Proceedings of the International Joint Conference on Neural Networks, 2023

2020

Random Forest for Dissimilarity-based Multi-view Learning.

Simon Bernard, Hongliu Cao, Robert Sabourin, Laurent Heutte

CoRR, 2020

A Novel Random Forest Dissimilarity Measure for Multi-View Learning.

Hongliu Cao, Simon Bernard, Robert Sabourin, Laurent Heutte

Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019

Random forest dissimilarity based multi-view learning for Radiomics application.

Hongliu Cao, Simon Bernard, Robert Sabourin, Laurent Heutte

Pattern Recognit., 2019

2018

Dissimilarity-based representation for radiomics applications.

Hongliu Cao, Simon Bernard, Laurent Heutte, Robert Sabourin

CoRR, 2018

Dynamic Voting in Multi-view Learning for Radiomics Applications.

Hongliu Cao, Simon Bernard, Laurent Heutte, Robert Sabourin

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

Improve the Performance of Transfer Learning Without Fine-Tuning Using Dissimilarity-Based Multi-view Learning for Breast Cancer Histology Images.

Hongliu Cao, Simon Bernard, Laurent Heutte, Robert Sabourin

Proceedings of the Image Analysis and Recognition - 15th International Conference, 2018

2016

The Multiclass ROC Front method for cost-sensitive classification.

Simon Bernard, Clément Chatelain, Sébastien Adam, Robert Sabourin

Pattern Recognit., 2016

ROC-based cost-sensitive classification with a reject option.

Clément Dubos, Simon Bernard, Sébastien Adam, Robert Sabourin

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

2013

One class random forests.

Chesner Désir, Simon Bernard, Caroline Petitjean, Laurent Heutte

Pattern Recognit., 2013

2012

Dynamic Random Forests.

Simon Bernard, Sébastien Adam, Laurent Heutte

Pattern Recognit. Lett., 2012

A New Random Forest Method for One-Class Classification.

Chesner Désir, Simon Bernard, Caroline Petitjean, Laurent Heutte

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2012

A Random Forest Based Approach for One Class Classification in Medical Imaging.

Chesner Désir, Simon Bernard, Caroline Petitjean, Laurent Heutte

Proceedings of the Machine Learning in Medical Imaging - Third International Workshop, 2012

2010

A Study of Strength and Correlation in Random Forests.

Simon Bernard, Laurent Heutte, Sébastien Adam

Proceedings of the Advanced Intelligent Computing Theories and Applications, 2010

2009

Forêts Aléatoires: De l'Analyse des Mécanismes de Fonctionnement à la Construction Dynamique. (Random Forests: From the Study of Behaviors to Dynamic Induction).

Simon Bernard

PhD thesis, 2009

Influence of Hyperparameters on Random Forest Accuracy.

Simon Bernard, Laurent Heutte, Sébastien Adam

Proceedings of the Multiple Classifier Systems, 8th International Workshop, 2009

On the selection of decision trees in Random Forests.

Simon Bernard, Laurent Heutte, Sébastien Adam

Proceedings of the International Joint Conference on Neural Networks, 2009

Towards a Better Understanding of Random Forests through the Study of Strength and Correlation.

Simon Bernard, Laurent Heutte, Sébastien Adam

Proceedings of the Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence, 2009

2008

Forest-RK: A New Random Forest Induction Method.

Simon Bernard, Laurent Heutte, Sébastien Adam

Proceedings of the Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence, 2008

2007

Using Random Forests for Handwritten Digit Recognition.

Simon Bernard, Sébastien Adam, Laurent Heutte

Proceedings of the 9th International Conference on Document Analysis and Recognition (ICDAR 2007), 2007