| Improving fairness generalization through a sample-robust optimization method J Ferry, U Aivodji, S Gambs, MJ Huguet, M Siala Machine Learning 112 (6), 2131-2192, 2023 | 19 | 2023 |
| Exploiting fairness to enhance sensitive attributes reconstruction J Ferry, U Aïvodji, S Gambs, MJ Huguet, M Siala 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 18-41, 2023 | 18 | 2023 |
| Learning fair rule lists U Aıvodji, J Ferry, S Gambs, MJ Huguet, M Siala arXiv preprint arXiv:1909.03977, 2019 | 15 | 2019 |
| Learning optimal fair scoring systems for multi-class classification J Rouzot, J Ferry, MJ Huguet 2022 IEEE 34th International Conference on Tools with Artificial …, 2022 | 14 | 2022 |
| Faircorels, an open-source library for learning fair rule lists U Aïvodji, J Ferry, S Gambs, MJ Huguet, M Siala Proceedings of the 30th ACM International Conference on Information …, 2021 | 14 | 2021 |
| Learning hybrid interpretable models: Theory, taxonomy, and methods J Ferry, G Laberge, U Aïvodji arXiv preprint arXiv:2303.04437, 2023 | 9 | 2023 |
| Probabilistic dataset reconstruction from interpretable models J Ferry, U Aïvodji, S Gambs, MJ Huguet, M Siala 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 1-17, 2024 | 8 | 2024 |
| SoK: Taming the Triangle--On the Interplays between Fairness, Interpretability and Privacy in Machine Learning J Ferry, U Aïvodji, S Gambs, MJ Huguet, M Siala arXiv preprint arXiv:2312.16191, 2023 | 7 | 2023 |
| Trained random forests completely reveal your dataset J Ferry, R Fukasawa, T Pascal, T Vidal arXiv preprint arXiv:2402.19232, 2024 | 6 | 2024 |
| Leveraging integer linear programming to learn optimal fair rule lists U Aïvodji, J Ferry, S Gambs, MJ Huguet, M Siala International Conference on Integration of Constraint Programming …, 2022 | 5 | 2022 |
| Addressing interpretability fairness & privacy in machine learning through combinatorial optimization methods J Ferry Université Paul Sabatier-Toulouse III, 2023 | 3 | 2023 |
| Training Set Reconstruction from Differentially Private Forests: How Effective is DP? A Gorgé, J Ferry, S Gambs, T Vidal arXiv preprint arXiv:2502.05307, 2025 | | 2025 |
| From Counterfactuals to Trees: Competitive Analysis of Model Extraction Attacks A Khouna, J Ferry, T Vidal arXiv preprint arXiv:2502.05325, 2025 | | 2025 |
| Fairness and Sparsity within Rashomon sets: Enumeration-Free Exploration and Characterization L Langlade, J Ferry, G Laberge, T Vidal arXiv preprint arXiv:2502.05286, 2025 | | 2025 |
| Smooth Sensitivity for Learning Differentially-Private yet Accurate Rule Lists T Ly, J Ferry, MJ Huguet, S Gambs, U Aivodji arXiv preprint arXiv:2403.13848, 2024 | | 2024 |
| Exploiter l'équité d'un modèle d'apprentissage pour reconstruire les attributs sensibles de son ensemble d'entraînement J Ferry, U Aïvodji, S Gambs, MJ Huguet, M Siala Rencontres des Jeunes Chercheurs en Intelligence Artificielle (RJCIA/PFIA 2023), 2023 | | 2023 |
| Interpretable and Differentially Private Machine Learning U Aıvodji, J Ferry, S Gambs, MJ Huguet, M Siala | | 2022 |
| Improving Fairness Generalization Through a Sample-Robust Optimization Method U Aıvodji, J Ferry, S Gambs, MJ Huguet, M Siala | | 2022 |
| Concilier l'équité statistique et la précision en apprentissage machine interprétable grâce à la PLNE J Ferry, U Aïvodji, S Gambs, MJ Huguet, M Siala 23ème congrès annuel de la Société Française de Recherche Opérationnelle et …, 2022 | | 2022 |
| Améliorer la généralisation de l'équité en apprentissage grâce à l'Optimisation Distributionnellement Robuste J Ferry, U Aïvodji, S Gambs, MJ Huguet, M Siala Rencontres des Jeunes Chercheurs en Intelligence Artificielle (RJCIA/PFIA 2021), 2021 | | 2021 |
Sébastien GambsUniversité du Québec à Montréal (UQAM)Email được xác minh tại uqam.ca