An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. - Rémi Viola; Rémi Emonet; Amaury Habrard; Guillaume Metzler; Sébastien Riou; Marc Sebban (ICTAI, 2019)

Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data. - Rémi Viola; Rémi Emonet; Amaury Habrard; Guillaume Metzler; Marc Sebban (IJCAI, 2020)

A Nearest Neighbor Algorithm for Imbalanced Classification. - Rémi Viola; Rémi Emonet; Amaury Habrard; Guillaume Metzler; Sébastien Riou; Marc Sebban (Int. J. Artif. Intell. Tools, 2021)

MetaAP: A meta-tree-based ranking algorithm optimizing the average precision from imbalanced data. - Rémi Viola; Léo Gautheron; Amaury Habrard; Marc Sebban (Pattern Recognit. Lett., 2022)

Highly imbalanced learning, application to fraud detection. (Apprentissage fortement déséquilibré, application à la détection de fraude). - Rémi Viola (2022)