Enrico Giampieri

Leveraging biased FedSDS as a federated learning strategy for research on non-IID multi-disorder studies

Abstract Federated learning is a powerful approach to overcome privacy and data sharing issues, especially in small sample healthcare settings. However, parameter aggregation strategies, such as FedAvg, are prone to fail in case of non-IID data distributions, which often arise in...