Stephane Maag

Re-Evaluating Privacy in Centralized and Decentralized Learning: An Information-Theoretical and Empirical Study

Decentralized Federated Learning (DFL) has garnered attention for its robustness and scalability compared to Centralized Federated Learning (CFL). While DFL is commonly believed to offer privacy advantages due to the decentralized control of sensitive data, recent work by Pasquini et, al. challenges…