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Ferry Julien
Ferry Julien
Postdoctoral Fellow, Polytechnique Montréal
Verified email at polymtl.ca - Homepage
Title
Cited by
Cited by
Year
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
152023
Learning fair rule lists
U Aıvodji, J Ferry, S Gambs, MJ Huguet, M Siala
arXiv preprint arXiv:1909.03977, 2019
142019
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
132021
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
122023
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
102022
Learning hybrid interpretable models: Theory, taxonomy, and methods
J Ferry, G Laberge, U Aïvodji
arXiv preprint arXiv:2303.04437, 2023
82023
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
62024
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
52022
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
32023
Addresing interpretability fairness & privacy in machine learning through combinatorial optimization methods
J Ferry
Université Paul Sabatier-Toulouse III, 2023
12023
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
Trained Random Forests Completely Reveal your Dataset
J Ferry, R Fukasawa, T Pascal, T Vidal
arXiv preprint arXiv:2402.19232, 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
Optimisation Distributionnellement Robuste pour améliorer la généralisation de l’équité en apprentissage
J Ferry, U Aïvodji, S Gambs, MJ Huguet, M Siala
2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)| 979-8-3503-4950-4/24/$31.00© 2024 IEEE| DOI: 10.1109/SaTML59370. 2024.00043
U Aïvodji, G Anderson, R Anderson, S Aydore, A Azize, D Basu, ...
SaTML 2024
J Ferry, U Aïvodji, S Gambs
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