Fraboni, Yann

4 publications

AISTATS 2024 SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization Yann Fraboni, Martin Van Waerebeke, Kevin Scaman, Richard Vidal, Laetitia Kameni, Marco Lorenzi

JMLR 2023 A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi

AISTATS 2021 Free-Rider Attacks on Model Aggregation in Federated Learning Yann Fraboni, Richard Vidal, Marco Lorenzi

ICML 2021 Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi