| 2026 | EACL | Lightweight Domain-Specific Language Model for Real-Time Structuring of Medical Prescriptions. | Jonathan Pattin Cottet, Vronique Eglin, Alex Aussem |
| 2023 | FlAIRS | Answering Student Queries with a Supervised Memory Conversational Agent. | Florian Baud, Alex Aussem |
| 2023 | RANLP | Non-Parametric Memory Guidance for Multi-Document Summarization. | Florian Baud, Alex Aussem |
| 2021 | ICDAR | Data-Efficient Information Extraction from Documents with Pre-trained Language Models. | Clment Sage, Thibault Douzon, Alex Aussem, Vronique Eglin, Haytham Elghazel, Stefan Duffner, Christophe Garcia, Jrmy Espinas |
| 2019 | IJCNN | Hierarchical Recurrent Attention Networks for Context-Aware Education Chatbots. | Jean-Baptiste Aujogue, Alex Aussem |
| 2017 | ESANN | Reducing variance due to importance weighting in covariate shift bias correction. | Van-Tinh Tran, Alex Aussem |
| 2016 | ICDM | Similarity Tree Pruning: A Novel Dynamic Ensemble Selection Approach. | Anil Narassiguin, Haytham Elghazel, Alex Aussem |
| 2015 | ICONIP | Calibrated k-labelsets for Ensemble Multi-label Classification. | Ouadie Gharroudi, Haytham Elghazel, Alex Aussem |
| 2015 | ICONIP | Correcting a Class of Complete Selection Bias with External Data Based on Importance Weight Estimation. | Van-Tinh Tran, Alex Aussem |
| 2015 | ICTAI | Ensemble Multi-label Classification: A Comparative Study on Threshold Selection and Voting Methods. | Ouadie Gharroudi, Haytham Elghazel, Alex Aussem |
| 2014 | AI | A Comparison of Multi-Label Feature Selection Methods Using the Random Forest Paradigm. | Ouadie Gharroudi, Haytham Elghazel, Alex Aussem |
| 2011 | ICDM | Semi-supervised Feature Importance Evaluation with Ensemble Learning. | Hasna Barkia, Haytham Elghazel, Alex Aussem |
| 2010 | ICDM | Feature Selection for Unsupervised Learning Using Random Cluster Ensembles. | Haytham Elghazel, Alex Aussem |
| 2009 | ECSQARU | Robust Gene Selection from Microarray Data with a Novel Markov Boundary Learning Method: Application to Diabetes Analysis. | Alex Aussem, Sergio Rodrigues de Morais, Florence Perraud, Sophie Rome |
| 2009 | IDA | Exploiting Data Missingness in Bayesian Network Modeling. | Sergio Rodrigues de Morais, Alex Aussem |
| 2009 | IDA | Incremental Bayesian Network Learning for Scalable Feature Selection. | Grgory Thibault, Alex Aussem, Stphane Bonnevay |
| 2008 | ICDM | A Conservative Feature Subset Selection Algorithm with Missing Data. | Alex Aussem, Sergio Rodrigues de Morais |
| 2007 | AIME | Nasopharyngeal Carcinoma Data Analysis with a Novel Bayesian Network Skeleton Learning Algorithm. | Alex Aussem, Sergio Rodrigues de Morais, Marilys Corbex |
| 2003 | ICANN | Closed Loop Stability of FIR-Recurrent Neural Networks. | Alex Aussem |
| 2001 | ESANN | Segmentation of switching dynamics with a Hidden Markov Model of neural prediction experts. | Alex Aussem, C. Boutevin |
| 2000 | IJCNN | Sufficient Conditions for Error Back Flow Convergence in Dynamical Recurrent Neural Networks. | Alex Aussem |
| 2000 | IJCNN | Queuing Network Modeling with Distributed Neural Networks for Service Quality Estimation in B-ISDN Network. | Alex Aussem, Antoine Mahul, Raymond Marie |