According to our database1, Benoît Frénay
Legend:Book In proceedings Article PhD thesis Other
Label-noise-tolerant classification for streaming data.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
Reinforced Extreme Learning Machines for Fast Robust Regression in the Presence of Outliers.
IEEE Trans. Cybernetics, 2016
Learning Interpretability for Visualizations using Adapted Cox Models through a User Experiment.
Special issue on advances in learning with label noise.
Feature ranking in changing environments where new features are introduced.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Classification in the Presence of Label Noise: A Survey.
IEEE Trans. Neural Netw. Learning Syst., 2014
Pointwise probability reinforcements for robust statistical inference.
Neural Networks, 2014
Estimating mutual information for feature selection in the presence of label noise.
Computational Statistics & Data Analysis, 2014
Automatic correction of SVM for drifted data classification.
Proceedings of the 14èmes Journées Francophones Extraction et Gestion des Connaissances, 2014
A comprehensive introduction to label noise.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014
Valid interpretation of feature relevance for linear data mappings.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014
Uncertainty and label noise in machine learning.
PhD thesis, 2013
Is mutual information adequate for feature selection in regression?
Neural Networks, 2013
Feature selection for nonlinear models with extreme learning machines.
Theoretical and empirical study on the potential inadequacy of mutual information for feature selection in classification.
Risk Estimation and Feature Selection.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013
On the Potential Inadequacy of Mutual Information for Feature Selection.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012
Parameter-insensitive kernel in extreme learning for non-linear support vector regression.
Label Noise-Tolerant Hidden Markov Models for Segmentation: Application to ECGs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011
Using SVMs with randomised feature spaces: an extreme learning approach.
Proceedings of the ESANN 2010, 2010
2S2, a simple reinforcement learning scheme for two-player zero-sum Markov games.
Improving the transition modelling in hidden Markov models for ECG segmentation.
Proceedings of the ESANN 2009, 2009
QL2, a simple reinforcement learning scheme for two-player zero-sum Markov games.
Proceedings of the ESANN 2008, 2008