SLA${}^2$P: Self-supervised Anomaly Detection with Adversarial Perturbation

Yizhou Wang, Can Qin, Rongzhe Wei +3

Anomaly detection is a fundamental yet challenging problem in machine learning due to the lack of label information. In this work, we propose a novel and powerful framework, dubbed…