This paper investigates to what degree and magnitude tradeoffs exist bet...
Federated learning (FL) allows multiple clients to collaboratively train...
Designing machine learning algorithms that are accurate yet fair, not
di...
We develop a novel method for ensuring fairness in machine learning whic...
We tackle here a specific, still not widely addressed aspect, of AI
robu...
Skin lesions can be an early indicator of a wide range of infectious and...
Perturbation-based attacks, while not physically realizable, have been t...
Ensuring trusted artificial intelligence (AI) in the real world is an
cr...
Membership inference (MI) attacks affect user privacy by inferring wheth...
Searching for small objects in large images is currently challenging for...
Whilst adversarial attack detection has received considerable attention,...
We propose a loss function for generative adversarial networks (GANs) us...
We focus on the development of effective adversarial patch attacks and –...
Few studies of deep learning systems (DLS) have addressed issues of
arti...
This work focuses on the ability to control via latent space factors sem...
Fast, collision-free motion through unknown environments remains a
chall...