Michaël Perrot

26 papers A* 7Journal 14Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Learning with Locally Private Examples by Inverse Weierstrass Private Stochastic Gradient Descent.
CoRR
Jean Dufraiche, Paul Mangold, Michaël Perrot, Marc Tommasi
2026 J jnl
Loss Gap Parity for Fairness in Heterogeneous Federated Learning.
CoRR
Brahim Erraji, Michaël Perrot, Aurélien Bellet
2025 J jnl
Fair Text Classification via Transferable Representations.
CoRR
Thibaud Leteno, Michaël Perrot, Charlotte Laclau, Antoine Gourru, Christophe Gravier
2025 J jnl
Fair Text Classification via Transferable Representations.
J. Mach. Learn. Res.
Thibaud Leteno, Michaël Perrot, Charlotte Laclau, Antoine Gourru, Christophe Gravier
2024 J jnl
On the Impact of Output Perturbation on Fairness in Binary Linear Classification.
CoRR
Vitalii Emelianov, Michaël Perrot
2024 J jnl
Recipient Profiling: Predicting Characteristics from Messages.
CoRR
Martin Borquez, Mikaela Keller, Michaël Perrot, Damien Sileo
2023 J jnl
A Revenue Function for Comparison-Based Hierarchical Clustering.
Trans. Mach. Learn. Res.
Aishik Mandal, Michaël Perrot, Debarghya Ghoshdastidar
2023 A* conf
Differential Privacy has Bounded Impact on Fairness in Classification.
ICML
Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi
2023 J jnl
FairGrad: Fairness Aware Gradient Descent.
Trans. Mach. Learn. Res.
Gaurav Maheshwari, Michaël Perrot
2022 J jnl
A Revenue Function for Comparison-Based Hierarchical Clustering.
CoRR
Aishik Mandal, Michaël Perrot, Debarghya Ghoshdastidar
2022 J jnl
FairGrad: Fairness Aware Gradient Descent.
CoRR
Gaurav Maheshwari, Michaël Perrot
2022 J jnl
Fairness Certificates for Differentially Private Classification.
CoRR
Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi
2022 A* conf
Optimal Tensor Transport.
AAAI
Tanguy Kerdoncuff, Rémi Emonet, Michaël Perrot, Marc Sebban
2020 A* conf
Near-Optimal Comparison Based Clustering.
NeurIPS
Michaël Perrot, Pascal Mattia Esser, Debarghya Ghoshdastidar
2020 J jnl
Near-Optimal Comparison Based Clustering.
CoRR
Michaël Perrot, Pascal Mattia Esser, Debarghya Ghoshdastidar
2020 A* conf
Too Relaxed to Be Fair.
ICML
Michael Lohaus, Michaël Perrot, Ulrike von Luxburg
2019 A* conf
Boosting for Comparison-Based Learning.
IJCAI
Michaël Perrot, Ulrike von Luxburg
2019 A* conf
Foundations of Comparison-Based Hierarchical Clustering.
NeurIPS
Debarghya Ghoshdastidar, Michaël Perrot, Ulrike von Luxburg
2018 J jnl
Boosting for Comparison-Based Learning.
CoRR
Michaël Perrot, Ulrike von Luxburg
2018 J jnl
Foundations of Comparison-Based Hierarchical Clustering.
CoRR
Debarghya Ghoshdastidar, Michaël Perrot, Ulrike von Luxburg
2016 — conf
Mapping Estimation for Discrete Optimal Transport.
NIPS
Michaël Perrot, Nicolas Courty, Rémi Flamary, Amaury Habrard
2016 — —
Theory and algorithms for learning metrics with controlled behaviour. (Théorie et algorithmes pour l'apprentissage de métriques à comportement contrôlé).
Michaël Perrot
2015 A* conf
A Theoretical Analysis of Metric Hypothesis Transfer Learning.
ICML
Michaël Perrot, Amaury Habrard
2015 — conf
Regressive Virtual Metric Learning.
NIPS
Michaël Perrot, Amaury Habrard
2014 — conf
Modeling Perceptual Color Differences by Local Metric Learning.
ECCV (5)
Michaël Perrot, Amaury Habrard, Damien Muselet, Marc Sebban
2012 — conf
Speeding Up Syntactic Learning Using Contextual Information.
ICGI
Leonor Becerra-Bonache, Élisa Fromont, Amaury Habrard, Michaël Perrot, Marc Sebban