most citedDiscriminative Adversarial Privacy: Balancing Accuracy and Membership Privacy in Neural Networks

2 citations · 2 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CR2023★ 2 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…