Alex Aussem
Orcid: 0000-0002-8797-5403
According to our database1,
Alex Aussem
authored at least 81 papers
between 1995 and 2023.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2023
Proceedings of the Actes de CORIA-TALN 2023. Actes de la 30e Conférence sur le Traitement Automatique des Langues Naturelles, TALN 2023, 2023
BERTEPro : A new Sentence Embedding Framework for the Education and Professional Training domain.
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023
Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, 2023
Proceedings of the Thirty-Sixth International Florida Artificial Intelligence Research Society Conference, 2023
Topic modeling neuronal non-paramétrique pour l'extraction d'insight client : une application à l'industrie du pneumatique.
Proceedings of the Extraction et Gestion des Connaissances, 2023
BERTEPro : Une nouvelle approche de représentation sémantique dans le domaine de l'éducation et de la formation professionnelle.
Proceedings of the Extraction et Gestion des Connaissances, 2023
Répondre aux requêtes des étudiants avec un agent conversationnel à mémoire supervisée.
Proceedings of the Extraction et Gestion des Connaissances, 2023
2022
Nonparametric neural topic modeling for customer insight extraction about the tire industry.
Proceedings of the International Joint Conference on Neural Networks, 2022
Proceedings of the Extraction et Gestion des Connaissances, 2022
2021
Proceedings of the Modeling Decisions for Artificial Intelligence, 2021
Data-Efficient Information Extraction from Documents with Pre-trained Language Models.
Proceedings of the Document Analysis and Recognition, 2021
2020
End-to-End Extraction of Structured Information from Business Documents with Pointer-Generator Networks.
Proceedings of the Fourth Workshop on Structured Prediction for NLP@EMNLP 2020, 2020
2019
Proceedings of the International Joint Conference on Neural Networks, 2019
Proceedings of the 2019 International Conference on Document Analysis and Recognition, 2019
2018
On the use of binary stochastic autoencoders for multi-label classification under the zero-one loss.
Proceedings of the INNS Conference on Big Data and Deep Learning 2018, 2018
2017
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017
2016
An extensive empirical comparison of ensemble learning methods for binary classification.
Pattern Anal. Appl., 2016
Ensemble multi-label text categorization based on rotation forest and latent semantic indexing.
Expert Syst. Appl., 2016
F-Measure Maximization in Multi-Label Classification with Conditionally Independent Label Subsets.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016
Identifying the irreducible disjoint factors of a multivariate probability distribution.
Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016
2015
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015
Ensemble Multi-label Classification: A Comparative Study on Threshold Selection and Voting Methods.
Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015
Correcting a Class of Complete Selection Bias with External Data Based on Importance Weight Estimation.
Proceedings of the Neural Information Processing - 22nd International Conference, 2015
Proceedings of the Neural Information Processing - 22nd International Conference, 2015
On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property.
Proceedings of the 32nd International Conference on Machine Learning, 2015
2014
A hybrid algorithm for Bayesian network structure learning with application to multi-label learning.
Expert Syst. Appl., 2014
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2014
A Comparison of Multi-Label Feature Selection Methods Using the Random Forest Paradigm.
Proceedings of the Advances in Artificial Intelligence, 2014
2013
Learning the local Bayesian network structure around the ZNF217 oncogene in breast tumours.
Comput. Biol. Medicine, 2013
2012
Pattern Recognit. Lett., 2012
Artif. Intell. Medicine, 2012
An Experimental Comparison of Hybrid Algorithms for Bayesian Network Structure Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012
2011
Trading-Off Diversity and Accuracy for Optimal Ensemble Tree Selection in Random Forests.
Proceedings of the Ensembles in Machine Learning Applications, 2011
Proceedings of the 11th IEEE International Conference on Data Mining, 2011
2010
Neurocomputing, 2010
Neurocomputing, 2010
Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks.
BMC Bioinform., 2010
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010
Proceedings of the ICDM 2010, 2010
Proceedings of the Apprentissage Artificiel et Fouille de Données, 2010
2009
Proceedings of the Advances in Intelligent Data Analysis VIII, 2009
Proceedings of the Advances in Intelligent Data Analysis VIII, 2009
Graph-Based Analysis of Nasopharyngeal Carcinoma with Bayesian Network Learning Methods.
Proceedings of the Graph-Based Representations in Pattern Recognition, 2009
Robust Gene Selection from Microarray Data with a Novel Markov Boundary Learning Method: Application to Diabetes Analysis.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2009
2008
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008
Proceedings of the Extraction et gestion des connaissances (EGC'2008), 2008
Handling almost-deterministic relationships in constraint-based Bayesian network discovery : Application to cancer risk factor identification.
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008
Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008
2007
Analysis of Nasopharyngeal Carcinoma Data with a Novel Bayesian Network Learning Algorithm.
Proceedings of the 2007 IEEE International Conference on Research, 2007
Learning Bayesian network structures by estimation of distribution algorithms: An experimental analysis.
Proceedings of the Second IEEE International Conference on Digital Information Management (ICDIM), 2007
A novel Bayesian Network structure learning algorithm based on minimal correlated itemset mining techniques.
Proceedings of the Second IEEE International Conference on Digital Information Management (ICDIM), 2007
Approche connexionniste pour l'extraction de profils cas-témoins du cancer du Nasopharynx à partir des données issues d'une étude épidémiologique.
Proceedings of the Extraction et gestion des connaissances (EGC'2007), 2007
Application des réseaux bayésiens à l'analyse des facteurs impliqués dans le cancer du Nasopharynx.
Proceedings of the Extraction et gestion des connaissances (EGC'2007), 2007
Nasopharyngeal Carcinoma Data Analysis with a Novel Bayesian Network Skeleton Learning Algorithm.
Proceedings of the Artificial Intelligence in Medicine, 2007
2006
Apprentissage de la structure des réseaux bayésiens à partir des motifs fréquents corrélés : application à l'identification des facteurs environnementaux du cancer du Nasopharynx.
Proceedings of the Extraction et gestion des connaissances (EGC'2006), 2006
Probabilistic classifiers and time-scale representations: application to the monitoring of a tramway guiding system.
Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006
Learning with monotonicity requirements for optimal routing with end-to-end quality of service constraints.
Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006
Modelling switching dynamics using prediction experts operating on distinct wavelet scales.
Proceedings of the 14th European Symposium on Artificial Neural Networks, 2006
2003
Distributed Neural Networks for Quality of Service Estimation in Communication Networks.
Int. J. Comput. Intell. Appl., 2003
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003
2002
Sufficient Conditions for Error Backflow Convergence in Dynamical Recurrent Neural Networks.
Neural Comput., 2002
e-functional dependency inference: application to DNA microarray expression data.
Proceedings of the 18èmes Journées Bases de Données Avancées, 2002
Le Calcul du Gradient d'Erreur dans les Réseaux de Neurones : Applications aux Telecom et aux Sciences Environnementales.
, 2002
2001
Int. J. Intell. Syst., 2001
Segmentation of switching dynamics with a Hidden Markov Model of neural prediction experts.
Proceedings of the 9th European Symposium on Artificial Neural Networks, 2001
2000
Neural-network metamodelling for the prediction of Caulerpa taxifolia development in the Mediterranean sea.
Neurocomputing, 2000
Queuing Network Modeling with Distributed Neural Networks for Service Quality Estimation in B-ISDN Network.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000
Sufficient Conditions for Error Back Flow Convergence in Dynamical Recurrent Neural Networks.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000
1999
Dynamical recurrent neural networks towards prediction and modeling of dynamical systems.
Neurocomputing, 1999
1998
Data Imputation and Nowcasting in the Environmental Sciences Using Clustering and Connectionist Modelling.
Proceedings of the COMPSTAT 1998, 1998
1997
Connect. Sci., 1997
1996
Fuzzy astronomical seeing nowcasts with a dynamical and recurrent connectionist network.
Neurocomputing, 1996
1995
Int. J. Neural Syst., 1995