Frénay Benoît
Frénay Benoît
Faculty of Computer Science, Université de Namur
Verified email at unamur.be - Homepage
Title
Cited by
Cited by
Year
Classification in the presence of label noise: a survey
B Frénay, M Verleysen
IEEE transactions on neural networks and learning systems 25 (5), 845-869, 2013
8882013
Using SVMs with randomised feature spaces: an extreme learning approach.
B Frénay, M Verleysen
ESANN, 2010
1242010
Parameter-insensitive kernel in extreme learning for non-linear support vector regression
B Frénay, M Verleysen
Neurocomputing 74 (16), 2526-2531, 2011
842011
Feature selection for nonlinear models with extreme learning machines
FN BenoíT, M Van Heeswijk, Y Miche, M Verleysen, A Lendasse
Neurocomputing 102, 111-124, 2013
812013
Interpretability of machine learning models and representations: an introduction.
A Bibal, B Frénay
ESANN, 2016
732016
A comprehensive introduction to label noise.
B Frénay, A Kabán
ESANN, 2014
602014
Clustering patterns of urban built-up areas with curves of fractal scaling behaviour
I Thomas, P Frankhauser, B Frenay, M Verleysen
Environment and Planning B: Planning and Design 37 (5), 942-954, 2010
602010
Is mutual information adequate for feature selection in regression?
B Frénay, G Doquire, M Verleysen
Neural Networks 48, 1-7, 2013
482013
Supervised ECG delineation using the wavelet transform and hidden Markov models
G de Lannoy, B Frénay, M Verleysen, J Delbeke
4th European Conference of the International Federation for Medical and …, 2009
462009
Theoretical and empirical study on the potential inadequacy of mutual information for feature selection in classification
BT FréNay, G Doquire, M Verleysen
Neurocomputing 112, 64-78, 2013
392013
Estimating mutual information for feature selection in the presence of label noise
B Frénay, G Doquire, M Verleysen
Computational Statistics & Data Analysis 71, 832-848, 2014
272014
Ensembles of local linear models for bankruptcy analysis and prediction
L Kainulainen, Y Miche, E Eirola, Q Yu, B Frénay, E Séverin, A Lendasse
Case Studies In Business, Industry And Government Statistics 4 (2), 116-133, 2014
202014
Label noise-tolerant hidden Markov models for segmentation: application to ECGs
B Frénay, G de Lannoy, M Verleysen
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
162011
Reinforced extreme learning machines for fast robust regression in the presence of outliers
B Frénay, M Verleysen
IEEE transactions on cybernetics 46 (12), 3351-3363, 2015
152015
On the Potential Inadequacy of Mutual Information for Feature Selection
B Frénay, G Doquire, M Verleysen
112012
Valid interpretation of feature relevance for linear data mappings
B Fránay, D Hofmann, A Schulz, M Biehl, B Hammer
2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM …, 2014
92014
Uncertainty and label noise in machine learning.
B Frénay
Catholic University of Louvain, Louvain-la-Neuve, Belgium, 2013
92013
Emission modelling for supervised ECG segmentation using finite differences
B Frénay, G de Lannoy, M Verleysen
4th European Conference of the International Federation for Medical and …, 2009
92009
Improving the transition modelling in hidden Markov models for ECG segmentation.
B Frénay, G De Lannoy, M Verleysen
ESANN, 2009
72009
Finding the most interpretable MDS rotation for sparse linear models based on external features.
A Bibal, R Marion, B Frénay
ESANN, 2018
62018
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