Alex Aussem

Emmanuel Prestat, Sergio Rodrigues de Morais, Julie A. Vendrell, Aurélie Thollet, Christian Gautier, Pascale A. Cohen, Alex Aussem: Learning the local Bayesian network structure around the ZNF217 oncogene in breast tumours. Comp. in Bio. and Med. 43(4): 334-341 (2013)

Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex: Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks. Artificial Intelligence in Medicine 54(1): 53-62 (2012)

Fazia Bellal, Haytham Elghazel, Alex Aussem: A semi-supervised feature ranking method with ensemble learning. Pattern Recognition Letters 33(10): 1426-1432 (2012)

Maxime Gasse, Alex Aussem, Haytham Elghazel: An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning. ECML/PKDD (1) 2012: 58-73

Hasna Barkia, Haytham Elghazel, Alex Aussem: Semi-supervised Feature Importance Evaluation with Ensemble Learning. ICDM 2011: 31-40

Haytham Elghazel, Alex Aussem, Florence Perraud: Trading-Off Diversity and Accuracy for Optimal Ensemble Tree Selection in Random Forests. Ensembles in Machine Learning Applications 2011: 169-179

Alex Aussem, André Tchernof, Sergio Rodrigues de Morais, Sophie Rome: Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks. BMC Bioinformatics 11: 487 (2010)

Alex Aussem: Bayesian networks. Neurocomputing 73(4-6): 561-562 (2010)

Sergio Rodrigues de Morais, Alex Aussem: A novel Markov boundary based feature subset selection algorithm. Neurocomputing 73(4-6): 578-584 (2010)

Alex Aussem, Sergio Rodrigues de Morais: A conservative feature subset selection algorithm with missing data. Neurocomputing 73(4-6): 585-590 (2010)

Haytham Elghazel, Alex Aussem: Feature Selection for Unsupervised Learning Using Random Cluster Ensembles. ICDM 2010: 168-175

Sergio Rodrigues de Morais, Alex Aussem: An Efficient and Scalable Algorithm for Local Bayesian Network Structure Discovery. ECML/PKDD (3) 2010: 164-179

Alex Aussem, Sergio Rodrigues de Morais, Florence Perraud, Sophie Rome: Robust Gene Selection from Microarray Data with a Novel Markov Boundary Learning Method: Application to Diabetes Analysis. ECSQARU 2009: 724-735

Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex, Joël Favrel: Graph-Based Analysis of Nasopharyngeal Carcinoma with Bayesian Network Learning Methods. GbRPR 2009: 52-61

Sergio Rodrigues de Morais, Alex Aussem: Exploiting Data Missingness in Bayesian Network Modeling. IDA 2009: 35-46

Grégory Thibault, Alex Aussem, Stéphane Bonnevay: Incremental Bayesian Network Learning for Scalable Feature Selection. IDA 2009: 202-212

Sergio Rodrigues de Morais, Alexandre Aussem, Marilys Corbex: Handling almost-deterministic relationships in constraint-based Bayesian network discovery : Application to cancer risk factor identification. ESANN 2008: 101-106

Fazia Bellal, Khalid Benabdeslem, Alexandre Aussem: SOM based clustering with instance-level constraints. ESANN 2008: 313-318

Anouar BenaHassena, Khalid Benabdeslem, Fazia Bellal, Alexandre Aussem, Bruno Canitia: Intégration de contraintes dans les cartes auto-organisatrices. EGC 2008: 643-648

Alex Aussem, Sergio Rodrigues de Morais: A Conservative Feature Subset Selection Algorithm with Missing Data. ICDM 2008: 725-730

Sergio Rodrigues de Morais, Alex Aussem: A Novel Scalable and Data Efficient Feature Subset Selection Algorithm. ECML/PKDD (2) 2008: 298-312

Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex: Nasopharyngeal Carcinoma Data Analysis with a Novel Bayesian Network Skeleton Learning Algorithm. AIME 2007: 326-330

Alexandre Aussem, Sergio Rodrigues de Morais, Marilys Corbex: Application des réseaux bayésiens à l'analyse des facteurs impliqués dans le cancer du Nasopharynx. EGC 2007: 123-134

Khalid Benabdeslem, Mustapha Lebbah, Alexandre Aussem, Marilys Corbex: Approche connexionniste pour l'extraction de profils cas-témoins du cancer du Nasopharynx à partir des données issues d'une étude épidémiologique. EGC 2007: 445-454

Zahra Kebaili, Alex Aussem: A novel Bayesian Network structure learning algorithm based on minimal correlated itemset mining techniques. ICDIM 2007: 121-126

Grégory Thibault, Stéphane Bonnevay, Alexandre Aussem: Learning Bayesian network structures by estimation of distribution algorithms: An experimental analysis. ICDIM 2007: 127-132

Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex: Analysis of Nasopharyngeal Carcinoma Data with a Novel Bayesian Network Learning Algorithm. RIVF 2007: 281-288

Alexandre Aussem, Pierre Chainais: Modelling switching dynamics using prediction experts operating on distinct wavelet scales. ESANN 2006: 185-190

Antoine Mahul, Alexandre Aussem: Learning with monotonicity requirements for optimal routing with end-to-end quality of service constraints. ESANN 2006: 455-460

Zahra Hamou Mamar, Pierre Chainais, Alexandre Aussem: Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system. ESANN 2006: 659-664

Alexandre Aussem, Zahra Kebaili, Marilys Corbex, Fabien De Marchi: Apprentissage de la structure des réseaux bayésiens à partir des motifs fréquents corrélés : application à l'identification des facteurs environnementaux du cancer du Nasopharynx. EGC 2006: 651-662

Antoine Mahul, Alex Aussem: Distributed Neural Networks for Quality of Service Estimation in Communication Networks. International Journal of Computational Intelligence and Applications 3(3): 297-308 (2003)

Alex Aussem: Closed Loop Stability of FIR-Recurrent Neural Networks. ICANN 2003: 523-529

Alex Aussem: Sufficient Conditions for Error Backflow Convergence in Dynamical Recurrent Neural Networks. Neural Computation 14(8): 1907-1927 (2002)

Alex Aussem, Jean-Marc Petit: e-functional dependency inference: application to DNA microarray expression data. BDA 2002

Alex Aussem, Fionn Murtagh: Web traffic demand forecasting using wavelet-based multiscale decomposition. Int. J. Intell. Syst. 16(2): 215-236 (2001)

Alex Aussem, C. Boutevin: Segmentation of switching dynamics with a Hidden Markov Model of neural prediction experts. ESANN 2001: 251-256

Fionn Murtagh, G. Zheng, J. G. Campbell, Alex Aussem: Neural network modelling for environmental prediction. Neurocomputing 30(1-4): 65-70 (2000)

Alex Aussem, David Hill: Neural-network metamodelling for the prediction of Caulerpa taxifolia development in the Mediterranean sea. Neurocomputing 30(1-4): 71-78 (2000)

Alex Aussem, Antoine Mahul, Raymond Marie: Queuing Network Modeling with Distributed Neural Networks for Service Quality Estimation in B-ISDN Network. IJCNN (5) 2000: 392-397

Alex Aussem: Sufficient Conditions for Error Back Flow Convergence in Dynamical Recurrent Neural Networks. IJCNN (4) 2000: 577-582

Alex Aussem: Dynamical recurrent neural networks towards prediction and modeling of dynamical systems. Neurocomputing 28(1-3): 207-232 (1999)

Alex Aussem, Fionn Murtagh: Combining Neural Network Forecasts on Wavelet-transformed Time Series. Connect. Sci. 9(1): 113-122 (1997)

Alex Aussem, Fionn Murtagh, Marc Sarazin: Fuzzy astronomical seeing nowcasts with a dynamical and recurrent connectionist network. Neurocomputing 13(2-4): 359-373 (1996)

Alex Aussem, Fionn Murtagh, Marc Sarazin: Dynamical recurrent neural networks -- towards environmental time series prediction. Int. J. Neural Syst. 6(2): 145-170 (1995)