77 citations · 274 across the 26 of their papers we have counts for
6 papers · 1 filter
The MPI + CUDA Gaia AVU-GSR Parallel Solver Toward Next-generation Exascale Infrastructures
Valentina Cesare, Ugo Becciani, Alberto Vecchiato +4
We ported to the GPU with CUDA the Astrometric Verification Unit-Global Sphere Reconstruction (AVU-GSR) Parallel Solver developed for the ESA Gaia mission, by optimizing a previous…
Benchmarking FedAvg and FedCurv for Image Classification Tasks
Bruno Casella, Roberto Esposito, Carlo Cavazzoni +1
Classic Machine Learning techniques require training on data available in a single data lake. However, aggregating data from different owners is not always convenient for different…
Experimenting with Normalization Layers in Federated Learning on non-IID scenarios
Bruno Casella, Roberto Esposito, Antonio Sciarappa +2
Training Deep Learning (DL) models require large, high-quality datasets, often assembled with data from different institutions. Federated Learning (FL) has been emerging as a metho…
Model-Agnostic Federated Learning
Gianluca Mittone, Walter Riviera, Iacopo Colonnelli +2
Since its debut in 2016, Federated Learning (FL) has been tied to the inner workings of Deep Neural Networks (DNNs). On the one hand, this allowed its development and widespread us…
Experimenting with Emerging RISC-V Systems for Decentralised Machine Learning
Gianluca Mittone, Nicolò Tonci, Robert Birke +10
Decentralised Machine Learning (DML) enables collaborative machine learning without centralised input data. Federated Learning (FL) and Edge Inference are examples of DML. While to…
A Federated Learning Benchmark for Drug-Target Interaction
Gianluca Mittone, Filip Svoboda, Marco Aldinucci +2
Aggregating pharmaceutical data in the drug-target interaction (DTI) domain has the potential to deliver life-saving breakthroughs. It is, however, notoriously difficult due to reg…