4 papers
On the Tradeoffs of On-Device Generative Models in Federated Predictive Maintenance Systems
Usevalad Milasheuski, Piero Baraldi, Enrico Zio +1
Federated Learning (FL) has emerged as a promising paradigm for preserving client data ownership and control over distributed Internet of Things (IoT) environments. While discrimin…
Bayesian Federated Learning for Continual Training
Usevalad Milasheuski, Luca Barbieri, Sanaz Kianoush +2
Bayesian Federated Learning (BFL) enables uncertainty quantification and robust adaptation in distributed learning. In contrast to the frequentist approach, it estimates the poster…
A Federated Learning Platform as a Service for Advancing Stroke Management in European Clinical Centers
Diogo Reis Santos, Albert Sund Aillet, Antonio Boiano +10
The rapid evolution of artificial intelligence (AI) technologies holds transformative potential for the healthcare sector. In critical situations requiring immediate decision-makin…
On the Impact of Data Heterogeneity in Federated Learning Environments with Application to Healthcare Networks
Usevalad Milasheuski, Luca Barbieri, Bernardo Camajori Tedeschini +2
Federated Learning (FL) allows multiple privacy-sensitive applications to leverage their dataset for a global model construction without any disclosure of the information. One of t…