Alex Aussem

Publication Activity (10 Years)

Years Active: 1995-2023
Publications (10 Years): 15

Top Topics

Conditionally Independent

Bayesian Network Structure

Hybrid Algorithm

Ensemble Selection

Top Venues

Expert Syst. Appl.

Publications

Florian Baud, Alex Aussem
Non-Parametric Memory Guidance for Multi-Document Summarization. RANLP (2023)
Florian Baud, Alex Aussem
Non-Parametric Memory Guidance for Multi-Document Summarization. CoRR (2023)
Florian Baud, Alex Aussem
Answering Student Queries with a Supervised Memory Conversational Agent. FLAIRS (2023)
Clément Sage, Thibault Douzon, Alex Aussem, Véronique Eglin, Haytham Elghazel, Stefan Duffner, Christophe Garcia, Jérémy Espinas
Data-Efficient Information Extraction from Documents with Pre-trained Language Models. ICDAR Workshops (2) (2021)
Clément Sage, Alex Aussem, Véronique Eglin, Haytham Elghazel, Jérémy Espinas
End-to-End Extraction of Structured Information from Business Documents with Pointer-Generator Networks. SPNLP@EMNLP (2020)
Jean-Baptiste Aujogue, Alex Aussem
Hierarchical Recurrent Attention Networks for Context-Aware Education Chatbots. IJCNN (2019)
Denis Lecoeuche, Alex Aussem, Maxime Gasse
On the use of binary stochastic autoencoders for multi-label classification under the zero-one loss. INNS Conference on Big Data (2018)
Van-Tinh Tran, Alex Aussem
Reducing variance due to importance weighting in covariate shift bias correction. ESANN (2017)
Anil Narassiguin, Haytham Elghazel, Alex Aussem
Dynamic Ensemble Selection with Probabilistic Classifier Chains. ECML/PKDD (1) (2017)
Maxime Gasse, Alex Aussem
F-Measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets. ECML/PKDD (1) (2016)
Haytham Elghazel, Alex Aussem, Ouadie Gharroudi, Wafa Saadaoui
Ensemble multi-label text categorization based on rotation forest and latent semantic indexing. Expert Syst. Appl. 57 (2016)
Anil Narassiguin, Mohamed Bibimoune, Haytham Elghazel, Alex Aussem
An extensive empirical comparison of ensemble learning methods for binary classification. Pattern Anal. Appl. 19 (4) (2016)
Anil Narassiguin, Haytham Elghazel, Alex Aussem
Similarity Tree Pruning: A Novel Dynamic Ensemble Selection Approach. ICDM Workshops (2016)
Maxime Gasse, Alex Aussem
Identifying the irreducible disjoint factors of a multivariate probability distribution. Probabilistic Graphical Models (2016)
Maxime Gasse, Alex Aussem
F-measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets. CoRR (2016)
Ouadie Gharroudi, Haytham Elghazel, Alex Aussem
Calibrated k-labelsets for Ensemble Multi-label Classification. ICONIP (1) (2015)
Van-Tinh Tran, Alex Aussem
Correcting a Class of Complete Selection Bias with External Data Based on Importance Weight Estimation. ICONIP (3) (2015)
Ouadie Gharroudi, Haytham Elghazel, Alex Aussem
Ensemble Multi-label Classification: A Comparative Study on Threshold Selection and Voting Methods. ICTAI (2015)
Maxime Gasse, Alex Aussem, Haytham Elghazel
An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning. CoRR (2015)
Maxime Gasse, Alex Aussem, Haytham Elghazel
A hybrid algorithm for Bayesian network structure learning with application to multi-label learning. CoRR (2015)
Van-Tinh Tran, Alex Aussem
A Practical Approach to Reduce the Learning Bias Under Covariate Shift. ECML/PKDD (2) (2015)
Haytham Elghazel, Alex Aussem
Unsupervised feature selection with ensemble learning. Mach. Learn. 98 (1-2) (2015)
Ouadie Gharroudi, Haytham Elghazel, Alex Aussem
A Comparison of Multi-Label Feature Selection Methods Using the Random Forest Paradigm. Canadian Conference on AI (2014)
Maxime Gasse, Alex Aussem, Haytham Elghazel
A hybrid algorithm for Bayesian network structure learning with application to multi-label learning. Expert Syst. Appl. 41 (15) (2014)
Alex Aussem, Pascal Caillet, Zara Klemm, Maxime Gasse, Anne-Marie Schott, Michel Ducher
Analysis of risk factors of hip fracture with causal Bayesian networks. IWBBIO (2014)
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. Comput. Biol. Medicine 43 (4) (2013)
Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex
Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks. Artif. Intell. Medicine 54 (1) (2012)
Fazia Bellal, Haytham Elghazel, Alex Aussem
A semi-supervised feature ranking method with ensemble learning. Pattern Recognit. Lett. 33 (10) (2012)
Maxime Gasse, Alex Aussem, Haytham Elghazel
An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning. ECML/PKDD (1) (2012)
Hasna Barkia, Haytham Elghazel, Alex Aussem
Semi-supervised Feature Importance Evaluation with Ensemble Learning. ICDM (2011)
Sergio Rodrigues de Morais, Alex Aussem
A novel Markov boundary based feature subset selection algorithm. Neurocomputing 73 (4-6) (2010)
Alex Aussem
Bayesian networks. Neurocomputing 73 (4-6) (2010)
Sergio Rodrigues de Morais, Alex Aussem
An Efficient and Scalable Algorithm for Local Bayesian Network Structure Discovery. ECML/PKDD (3) (2010)
Alex Aussem, André Tchernof, Sergio Rodrigues de Morais, Sophie Rome
Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks. BMC Bioinform. 11 (2010)
Haytham Elghazel, Alex Aussem
Feature Selection for Unsupervised Learning Using Random Cluster Ensembles. ICDM (2010)
Alex Aussem, Sergio Rodrigues de Morais
A conservative feature subset selection algorithm with missing data. Neurocomputing 73 (4-6) (2010)
Grégory Thibault, Alex Aussem, Stéphane Bonnevay
Incremental Bayesian Network Learning for Scalable Feature Selection. IDA (2009)
Sergio Rodrigues de Morais, Alex Aussem
Exploiting Data Missingness in Bayesian Network Modeling. IDA (2009)
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)
Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex, Joël Favrel
Graph-Based Analysis of Nasopharyngeal Carcinoma with Bayesian Network Learning Methods. GbRPR (2009)
Alex Aussem, Sergio Rodrigues de Morais
A Conservative Feature Subset Selection Algorithm with Missing Data. ICDM (2008)
Sergio Rodrigues de Morais, Alex Aussem
A Novel Scalable and Data Efficient Feature Subset Selection Algorithm. ECML/PKDD (2) (2008)
Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex
Nasopharyngeal Carcinoma Data Analysis with a Novel Bayesian Network Skeleton Learning Algorithm. AIME (2007)
Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex
Analysis of Nasopharyngeal Carcinoma Data with a Novel Bayesian Network Learning Algorithm. RIVF (2007)
Zahra Kebaili, Alex Aussem
A novel Bayesian Network structure learning algorithm based on minimal correlated itemset mining techniques. ICDIM (2007)
Antoine Mahul, Alex Aussem
Distributed Neural Networks for Quality of Service Estimation in Communication Networks. Int. J. Comput. Intell. Appl. 3 (3) (2003)
Alex Aussem
Closed Loop Stability of FIR-Recurrent Neural Networks. ICANN (2003)
Alex Aussem, Jean-Marc Petit
e-functional dependency inference: application to DNA microarray expression data. BDA (2002)
Alex Aussem
Sufficient Conditions for Error Backflow Convergence in Dynamical Recurrent Neural Networks. Neural Comput. 14 (8) (2002)
Alex Aussem, C. Boutevin
Segmentation of switching dynamics with a Hidden Markov Model of neural prediction experts. ESANN (2001)
Alex Aussem, Fionn Murtagh
Web traffic demand forecasting using wavelet-based multiscale decomposition. Int. J. Intell. Syst. 16 (2) (2001)
David R. C. Hill, Patrick Coquillard, Alex Aussem, Jean de Vaugelas, Thierry Thibaut, Alexandre Meinesz
Modeling the Ultimate Seaweed Expansion. Simul. 76 (2) (2001)
Fionn Murtagh, G. Zheng, Jonathan G. Campbell, Alex Aussem
Neural network modelling for environmental prediction. Neurocomputing 30 (1-4) (2000)
Alex Aussem, David R. C. Hill
Neural-network metamodelling for the prediction of Caulerpa taxifolia development in the Mediterranean sea. Neurocomputing 30 (1-4) (2000)
Alex Aussem
Sufficient Conditions for Error Back Flow Convergence in Dynamical Recurrent Neural Networks. IJCNN (4) (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)
Alex Aussem
Dynamical recurrent neural networks towards prediction and modeling of dynamical systems. Neurocomputing 28 (1-3) (1999)
Fionn Murtagh, G. Zheng, Jonathan G. Campbell, Alex Aussem, M. Ouberdous, E. Demirov, Walter Eifler, M. Crépon
Data Imputation and Nowcasting in the Environmental Sciences Using Clustering and Connectionist Modelling. COMPSTAT (1998)
Alex Aussem, Fionn Murtagh
Combining Neural Network Forecasts on Wavelet-transformed Time Series. Connect. Sci. 9 (1) (1997)
Alex Aussem, Fionn Murtagh, Marc Sarazin
Fuzzy astronomical seeing nowcasts with a dynamical and recurrent connectionist network. Neurocomputing 13 (2-4) (1996)
Alex Aussem, Fionn Murtagh, Marc Sarazin
Dynamical recurrent neural networks -- towards environmental time series prediction. Int. J. Neural Syst. 6 (2) (1995)