Alex Aussem
Alex Aussem
Professor in Computer Science, Univ. Lyon 1, France
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Waveletbased feature extraction and decomposition strategies for financial forecasting
A Aussem
International Journal of Computational Intelligence in Finance 6, 5-12, 1998
Combining neural network forecasts on wavelet-transformed time series
A Aussem, F Murtagh
Connection Science 9 (1), 113-122, 1997
A hybrid algorithm for Bayesian network structure learning with application to multi-label learning
M Gasse, A Aussem, H Elghazel
Expert Systems with Applications 41 (15), 6755-6772, 2014
Dynamical recurrent neural networks—towards environmental time series prediction
A Aussem, F Murtagh, M Sarazin
International Journal of Neural Systems 6 (02), 145-170, 1995
Unsupervised feature selection with ensemble learning
H Elghazel, A Aussem
Machine Learning 98, 157-180, 2015
Dynamical recurrent neural networks towards prediction and modeling of dynamical systems
A Aussem
Neurocomputing 28 (1-3), 207-232, 1999
Ensemble multi-label text categorization based on rotation forest and latent semantic indexing
H Elghazel, A Aussem, O Gharroudi, W Saadaoui
Expert Systems with Applications 57, 1-11, 2016
A semi-supervised feature ranking method with ensemble learning
F Bellal, H Elghazel, A Aussem
Pattern Recognition Letters 33 (10), 1426-1433, 2012
A comparison of multi-label feature selection methods using the random forest paradigm
O Gharroudi, H Elghazel, A Aussem
Advances in Artificial Intelligence: 27th Canadian Conference on Artificial …, 2014
A novel scalable and data efficient feature subset selection algorithm
S Rodrigues de Morais, A Aussem
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008
A novel Markov boundary based feature subset selection algorithm
SR de Morais, A Aussem
Neurocomputing 73 (4-6), 578-584, 2010
An experimental comparison of hybrid algorithms for Bayesian network structure learning
M Gasse, A Aussem, H Elghazel
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012
A conservative feature subset selection algorithm with missing data
A Aussem, SR de Morais
Neurocomputing 73 (4-6), 585-590, 2010
Recurrent neural network approach for table field extraction in business documents
C Sage, A Aussem, H Elghazel, V Eglin, J Espinas
2019 International Conference on Document Analysis and Recognition (ICDAR …, 2019
A neuro-wavelet strategy for web traffic forecasting
A Aussem, F Murtagh
Research in Official Statistics 1 (1), 65-87, 1998
Feature selection for unsupervised learning using random cluster ensembles
H Elghazel, A Aussem
2010 IEEE International Conference on Data Mining, 168-175, 2010
Web traffic demand forecasting using wavelet‐based multiscale decomposition
A Aussem, F Murtagh
International Journal of Intelligent Systems 16 (2), 215-236, 2001
Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks
A Aussem, SRR De Morais, M Corbex
Artificial intelligence in Medicine 54 (1), 53-62, 2012
Dynamical recurrent neural networks and pattern recognition methods for time series prediction: application to seeing and temperature forecasting in the context of ESO's VLT …
A Aussem, F Murtagh, M Sarazin
Vistas in astronomy 38, 357-374, 1994
Semi-supervised feature importance evaluation with ensemble learning
H Barkia, H Elghazel, A Aussem
2011 IEEE 11th International Conference on Data Mining, 31-40, 2011
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