2 papers
stat.ML2020
Towards Deep Learning Models Resistant to Large Perturbations
Amirreza Shaeiri, Rozhin Nobahari, Mohammad Hossein Rohban
Adversarial robustness has proven to be a required property of machine learning algorithms. A key and often overlooked aspect of this problem is to try to make the adversarial nois…
cs.CV2020
ARAE: Adversarially Robust Training of Autoencoders Improves Novelty Detection
Mohammadreza Salehi, Atrin Arya, Barbod Pajoum +4
Autoencoders (AE) have recently been widely employed to approach the novelty detection problem. Trained only on the normal data, the AE is expected to reconstruct the normal data e…