| From Weakly Supervised Learning to Biquality Learning: an Introduction P Nodet, V Lemaire, A Bondu, A Cornuéjols, A Ouorou In Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2021 | 31 | 2021 |
| Importance Reweighting for Biquality Learning P Nodet, V Lemaire, A Bondu, A Cornuéjols, A Ouorou In Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2021 | 8 | 2021 |
| Contrastive representations for label noise require fine-tuning P Nodet, V Lemaire, A Bondu, A Cornuéjols arXiv preprint arXiv:2108.09154, 2021 | 2 | 2021 |
| Biquality learning: a framework to design algorithms dealing with closed-set distribution shifts P Nodet, V Lemaire, A Bondu, A Cornuéjols Machine Learning 112 (12), 4663-4692, 2023 | | 2023 |
| biquality-learn: a Python library for Biquality Learning P Nodet, V Lemaire, A Bondu, A Cornuéjols arXiv preprint arXiv:2308.09643, 2023 | | 2023 |
| Biquality learning: from weakly supervised learning to distribution shifts P Nodet Université Paris-Saclay, 2023 | | 2023 |
| Repondération Préférentielle pour l’Apprentissage Biqualité P Nodet, V Lemaire, A Bondu, A Cornuéjols Extraction et Gestion des Connaissances: EGC'2022 38, 2022 | | 2022 |
Vincent LemaireOrange LabsVerified email at orange.com
