23 citations · 26 across the 9 of their papers we have counts for
3 papers · 1 filter
Learning Dynamical Systems from Multiple Sparse Datasets: A Hierarchical Bayesian Modeling Approach
Cristian Brugnara, Lea Multerer, Marco Forgione +1
Estimating parameters of dynamical systems from sparse, noisy, and irregularly sampled data is often severely ill-conditioned. When multiple related datasets are available, they pr…
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…