| Waveletbased feature extraction and decomposition strategies for financial forecasting A Aussem International Journal of Computational Intelligence in Finance 6, 5-12, 1998 | 266 | 1998 |
| Combining neural network forecasts on wavelet-transformed time series A Aussem, F Murtagh Connection Science 9 (1), 113-122, 1997 | 162 | 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 | 89 | 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 | 84 | 1995 |
| Unsupervised feature selection with ensemble learning H Elghazel, A Aussem Machine Learning 98, 157-180, 2015 | 78 | 2015 |
| Dynamical recurrent neural networks towards prediction and modeling of dynamical systems A Aussem Neurocomputing 28 (1-3), 207-232, 1999 | 75 | 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 | 71 | 2016 |
| A semi-supervised feature ranking method with ensemble learning F Bellal, H Elghazel, A Aussem Pattern Recognition Letters 33 (10), 1426-1433, 2012 | 53 | 2012 |
| 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 | 48 | 2008 |
| 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 | 47 | 2014 |
| A novel Markov boundary based feature subset selection algorithm SR de Morais, A Aussem Neurocomputing 73 (4-6), 578-584, 2010 | 43 | 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 | 38 | 2012 |
| A conservative feature subset selection algorithm with missing data A Aussem, SR de Morais Neurocomputing 73 (4-6), 585-590, 2010 | 36 | 2010 |
| A neuro-wavelet strategy for web traffic forecasting A Aussem, F Murtagh Research in Official Statistics 1 (1), 65-87, 1998 | 32 | 1998 |
| 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 | 31 | 2019 |
| Feature selection for unsupervised learning using random cluster ensembles H Elghazel, A Aussem 2010 IEEE International Conference on Data Mining, 168-175, 2010 | 31 | 2010 |
| Web traffic demand forecasting using wavelet‐based multiscale decomposition A Aussem, F Murtagh International Journal of Intelligent Systems 16 (2), 215-236, 2001 | 30 | 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 | 29 | 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 | 29 | 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 | 28 | 2011 |
