Ta Li

RetFL: a privacy-preserving and traceable framework for robust federated learning

Federated learning (FL) enables multiple clients to jointly train a model without sharing raw data. Decentralized federated learning (DFL) further removes the need for a trusted central coordinator in the aggregation process. However, in decentralized settings, model aggregation is vulnerable to inference and poisoning...