194 citations · 246 across the 12 of their papers we have counts for
13 papers
An Informativeness-based Clustered Federated Learning Method for Reliable Traffic Prediction in Managed Wi-Fi Networks
Luca Barbieri, Gianluca Fontanesi, Lorenzo Galati Giordano +2
Centrally-managed Wi-Fi solutions are increasingly leveraging Distributed Artificial Intelligence (AI) to predict key operational statistics of Access Points (APs) and proactively…
Cluster-Specific Predictive Modeling: A Scalable Solution for Resource-Constrained Wi-Fi Controllers
Gianluca Fontanesi, Luca Barbieri, Lorenzo Galati Giordano +2
This manuscript presents a comprehensive analysis of predictive modeling optimization in managed Wi-Fi networks through the integration of clustering algorithms and model evaluatio…
Target Classification for Integrated Sensing and Communication in Industrial Deployments
Luca Barbieri, Marcus Henninger, Paolo Tosi +4
Integrated Sensing and Communication (ISAC) systems enable cellular networks to jointly operate as communication technology and sense the environment. While opportunities and poten…
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…
Compressed Bayesian Federated Learning for Reliable Passive Radio Sensing in Industrial IoT
Luca Barbieri, Stefano Savazzi, Monica Nicoli
Bayesian Federated Learning (FL) has been recently introduced to provide well-calibrated Machine Learning (ML) models quantifying the uncertainty of their predictions. Despite thei…
A Secure and Trustworthy Network Architecture for Federated Learning Healthcare Applications
Antonio Boiano, Marco Di Gennaro, Luca Barbieri +7
Federated Learning (FL) has emerged as a promising approach for privacy-preserving machine learning, particularly in sensitive domains such as healthcare. In this context, the TRUS…
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…
Deep Learning-based Cooperative LiDAR Sensing for Improved Vehicle Positioning
Luca Barbieri, Bernardo Camajori Tedeschini, Mattia Brambilla +1
Accurate positioning is known to be a fundamental requirement for the deployment of Connected Automated Vehicles (CAVs). To meet this need, a new emerging trend is represented by c…
A Carbon Tracking Model for Federated Learning: Impact of Quantization and Sparsification
Luca Barbieri, Stefano Savazzi, Sanaz Kianoush +2
Federated Learning (FL) methods adopt efficient communication technologies to distribute machine learning tasks across edge devices, reducing the overhead in terms of data storage…
Fast emitting nanocomposites for high-resolution ToF-PET imaging based on multicomponent scintillators
Matteo Orfano, Fiammetta Pagano, Ilaria Mattei +9
Time-of-Flight Positron Emission Tomography is a medical imaging technique, based on the detection of two back-to-back γ-photons generated from radiotracers injected in the body. I…
Channel-driven Decentralized Bayesian Federated Learning for Trustworthy Decision Making in D2D Networks
Luca Barbieri, Osvaldo Simeone, Monica Nicoli
Bayesian Federated Learning (FL) offers a principled framework to account for the uncertainty caused by limitations in the data available at the nodes implementing collaborative tr…
Opportunities of Federated Learning in Connected, Cooperative and Automated Industrial Systems
Stefano Savazzi, Monica Nicoli, Mehdi Bennis +2
Next-generation autonomous and networked industrial systems (i.e., robots, vehicles, drones) have driven advances in ultra-reliable, low latency communications (URLLC) and computin…