4 papers
Phyelds: A Pythonic Framework for Aggregate Computing
Gianluca Aguzzi, Davide Domini, Nicolas Farabegoli +1
Aggregate programming is a field-based coordination paradigm with over a decade of exploration and successful applications across domains including sensor networks, robotics, and I…
Sparse Self-Federated Learning for Energy Efficient Cooperative Intelligence in Society 5.0
Davide Domini, Laura Erhan, Gianluca Aguzzi +4
Federated Learning offers privacy-preserving collaborative intelligence but struggles to meet the sustainability demands of emerging IoT ecosystems necessary for Society 5.0-a huma…
ProFed: a Benchmark for Proximity-based non-IID Federated Learning
Davide Domini, Gianluca Aguzzi, Mirko Viroli
In recent years, cro:flFederated learning (FL) has gained significant attention within the machine learning community. Although various FL algorithms have been proposed in the lite…
FBFL: A Field-Based Coordination Approach for Data Heterogeneity in Federated Learning
Davide Domini, Gianluca Aguzzi, Lukas Esterle +1
In the last years, Federated learning (FL) has become a popular solution to train machine learning models in domains with high privacy concerns. However, FL scalability and perform…