Accenture Labs Sophia Antipolis Publications and Associated Code on Federated Learning

• Yann Fraboni, Richard Vidal, Marco Lorenzi. Free-rider Attacks on Model Aggregation in Federated Learning. AISTATS 2021
  • The paper can be found here.
  • The code can be found here.
• Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi. Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning. ICML 2021
  • The paper can be found here.
  • The code can be found here.
• Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi. A General Theory for Client Sampling in Federated Learning. FL-IJCAI'22
  • The paper can be found here.
  • The code can be found here.
• Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi. A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates. JMLR 2023
  • The paper can be found here.
  • The code can be found here.
• Yann Fraboni, Martin Van Waerebeke, Richard Vidal, Laetitia Kameni, Kevin Scaman, Marco Lorenzi. Sequential Informed Federated Unlearning: Efficient and Provable Client Unlearning in Federated Optimization. Preprint.
  • The paper can be found here.
  • The code can be found here.
• Yann Fraboni, Lucia Innocenti,Michela Antonelli, Richard Vidal, Laetitia Kameni, Sebastien Ourselin, Marco Lorenzi. Validation of Federated Learning on Collaborative Prostate Segmentation. MICCAI 2023 - DeCaF
  • The paper can be found here.
  • The code can be found here.