A Preprocessing Approach for Class-Imbalanced Data Using SMOTE and Belief Function Theory. - Fares Grina; Zied Elouedi; Eric Lefevre (IDEAL (2), 2020)

Uncertainty-Aware Resampling Method for Imbalanced Classification Using Evidence Theory. - Fares Grina; Zied Elouedi; Eric Lefèvre (ECSQARU, 2021)

Evidential Undersampling Approach for Imbalanced Datasets with Class-Overlapping and Noise. - Fares Grina; Zied Elouedi; Eric Lefevre (MDAI, 2021)

Evidential Hybrid Re-sampling for Multi-class Imbalanced Data. - Fares Grina; Zied Elouedi; Eric Lefevre (IPMU (2), 2022)

Déséquilibre multi-classes : une approche évidentielle de rééchantillonnage hybride. - Fares Grina; Zied Elouedi; Eric Lefèvre (LFA, 2022)

Learning from Imbalanced Data Using an Evidential Undersampling-Based Ensemble. - Fares Grina; Zied Elouedi; Eric Lefevre (SUM, 2022)

Evidential Generative Adversarial Networks for Handling Imbalanced Learning. - Fares Grina; Zied Elouedi; Eric Lefevre (ECSQARU, 2023)

Re-sampling of multi-class imbalanced data using belief function theory and ensemble learning. - Fares Grina; Zied Elouedi; Eric Lefevre (Int. J. Approx. Reason., 2023)