33 citations · 118 across the 17 of their papers we have counts for
3 papers · 1 filter
Federated Clustering: An Unsupervised Cluster-Wise Training for Decentralized Data Distributions
Mirko Nardi, Lorenzo Valerio, Andrea Passarella
Federated Learning (FL) enables decentralized machine learning while preserving data privacy, making it ideal for sensitive applications where data cannot be shared. While FL has b…
FedQUIT: On-Device Federated Unlearning via a Quasi-Competent Virtual Teacher
Alessio Mora, Lorenzo Valerio, Paolo Bellavista +1
Federated Learning (FL) enables the collaborative training of machine learning models without requiring centralized collection of user data. To comply with the right to be forgotte…
Impact of network topology on the performance of Decentralized Federated Learning
Luigi Palmieri, Chiara Boldrini, Lorenzo Valerio +2
Fully decentralized learning is gaining momentum for training AI models at the Internet's edge, addressing infrastructure challenges and privacy concerns. In a decentralized machin…