2 papers
cs.LG2024
ProFe: Communication-Efficient Decentralized Federated Learning via Distillation and Prototypes
Pedro Miguel Sánchez Sánchez, Enrique Tomás Martínez Beltrán, Miguel Fernández Llamas +3
Decentralized Federated Learning (DFL) trains models in a collaborative and privacy-preserving manner while removing model centralization risks and improving communication bottlene…
cs.DC2024
DART: A Solution for Decentralized Federated Learning Model Robustness Analysis
Chao Feng, Alberto Huertas Celdrán, Jan von der Assen +3
Federated Learning (FL) has emerged as a promising approach to address privacy concerns inherent in Machine Learning (ML) practices. However, conventional FL methods, particularly…