most citedBridging the Gap: Enhancing the Utility of Synthetic Data via Post-Processing Techniques

4 citations · 7 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2023

Age Group Discrimination via Free Handwriting Indicators

Eugenio Lomurno, Simone Toffoli, Davide Di Febbo +3

The growing global elderly population is expected to increase the prevalence of frailty, posing significant challenges to healthcare systems. Frailty, a syndrome associated with ag…

cs.CV20234 cited

Bridging the Gap: Enhancing the Utility of Synthetic Data via Post-Processing Techniques

Andrea Lampis, Eugenio Lomurno, Matteo Matteucci

Acquiring and annotating suitable datasets for training deep learning models is challenging. This often results in tedious and time-consuming efforts that can hinder research progr…

cs.CR20232 cited

Discriminative Adversarial Privacy: Balancing Accuracy and Membership Privacy in Neural Networks

Eugenio Lomurno, Alberto Archetti, Francesca Ausonio +1

The remarkable proliferation of deep learning across various industries has underscored the importance of data privacy and security in AI pipelines. As the evolution of sophisticat…

cs.LG20231 cited

Two Steps Forward and One Behind: Rethinking Time Series Forecasting with Deep Learning

Riccardo Ughi, Eugenio Lomurno, Matteo Matteucci

The Transformer is a highly successful deep learning model that has revolutionised the world of artificial neural networks, first in natural language processing and later in comput…

cs.LG2023

Heterogeneous Datasets for Federated Survival Analysis Simulation

Alberto Archetti, Eugenio Lomurno, Francesco Lattari +2

Survival analysis studies time-modeling techniques for an event of interest occurring for a population. Survival analysis found widespread applications in healthcare, engineering,…

cs.LG2023

Enhancing Once-For-All: A Study on Parallel Blocks, Skip Connections and Early Exits

Simone Sarti, Eugenio Lomurno, Andrea Falanti +1

The use of Neural Architecture Search (NAS) techniques to automate the design of neural networks has become increasingly popular in recent years. The proliferation of devices with…