10 citations · 11 across the 3 of their papers we have counts for
3 papers
On the Detectability of Active Gradient Inversion Attacks in Federated Learning
Vincenzo Carletti, Pasquale Foggia, Carlo Mazzocca +2
One of the key advantages of Federated Learning (FL) is its ability to collaboratively train a Machine Learning (ML) model while keeping clients' data on-site. However, this can cr…
GUIDE: Enhancing Gradient Inversion Attacks in Federated Learning with Denoising Models
Vincenzo Carletti, Pasquale Foggia, Carlo Mazzocca +2
Federated Learning (FL) enables collaborative training of Machine Learning (ML) models across multiple clients while preserving their privacy. Rather than sharing raw data, federat…
A Quadratic Assignment Formulation of the Graph Edit Distance
Sébastien Bougleux, Luc Brun, Vincenzo Carletti +3
Computing efficiently a robust measure of similarity or dissimilarity between graphs is a major challenge in Pattern Recognition. The Graph Edit Distance (GED) is a flexible measur…