6 citations · 7 across the 2 of their papers we have counts for
3 papers
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…
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…