2 papers
cs.LG2023
Preserving Privacy in GANs Against Membership Inference Attack
Mohammadhadi Shateri, Francisco Messina, Fabrice Labeau +1
Generative Adversarial Networks (GANs) have been widely used for generating synthetic data for cases where there is a limited size real-world dataset or when data holders are unwil…
cs.CV2022
MEAD: A Multi-Armed Approach for Evaluation of Adversarial Examples Detectors
Federica Granese, Marine Picot, Marco Romanelli +2
Detection of adversarial examples has been a hot topic in the last years due to its importance for safely deploying machine learning algorithms in critical applications. However, t…