Vidal, Richard

8 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 2023 Federated Learning for Data Streams Othmane Marfoq, Giovanni Neglia, Laetitia Kameni, Richard Vidal

ICML 2022 Personalized Federated Learning Through Local Memorization Othmane Marfoq, Giovanni Neglia, Richard Vidal, Laetitia Kameni

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

NeurIPS 2021 Federated Multi-Task Learning Under a Mixture of Distributions Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal

NeurIPS 2020 Throughput-Optimal Topology Design for Cross-Silo Federated Learning Othmane Marfoq, Chuan Xu, Giovanni Neglia, Richard Vidal