1 citations · 1 across the 5 of their papers we have counts for
5 papers
FPLIER: Federated Pathway-Level Information Extractor
Daniele Malpetti, Christian Berchtold, Francesco Gualdi +3
In transcriptomics, gene-set-aware factorization methods such as the Pathway Level Information Extractor (PLIER) are most effective when trained on large, heterogeneous expression…
Tiny-DroNeRF: Tiny Neural Radiance Fields aboard Federated Learning-enabled Nano-drones
Ilenia Carboni, Elia Cereda, Lorenzo Lamberti +3
Sub-30g nano-sized aerial robots can leverage their agility and form factor to autonomously explore cluttered and narrow environments, like in industrial inspection and search and…
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…
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…
Global Outlier Detection in a Federated Learning Setting with Isolation Forest
Daniele Malpetti, Laura Azzimonti
We present a novel strategy for detecting global outliers in a federated learning setting, targeting in particular cross-silo scenarios. Our approach involves the use of two server…