2 papers
q-bio.OT2025
Technical and Legal Aspects of Federated Learning in Bioinformatics: Applications, Challenges and Opportunities
Daniele Malpetti, Marco Scutari, Francesco Gualdi +6
Federated learning leverages data across institutions to improve clinical discovery while complying with data-sharing restrictions and protecting patient privacy. This paper provid…
cs.LG2024
Flotta: a Secure and Flexible Spark-inspired Federated Learning Framework
Claudio Bonesana, Daniele Malpetti, Sandra Mitrović +2
We present Flotta, a Federated Learning framework designed to train machine learning models on sensitive data distributed across a multi-party consortium conducting research in con…