1 citations · 1 across the 3 of their papers we have counts for
3 papers
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…
cs.LG2024★ 1 cited
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…
math.ST2020
An exact kernel framework for spatio-temporal dynamics
Oleg Szehr, Dario Azzimonti, Laura Azzimonti
A kernel-based framework for spatio-temporal data analysis is introduced that applies in situations when the underlying system dynamics are governed by a dynamic equation. The key…