Deep anomaly detection and search via reinforcement learning (student abstract)

Anomaly detection (AD) holds substantial practical value, and considering the limited labeled data, the semi-supervised anomaly detection technique has garnered increasing attention. We find that previous methods suffer from insufficient exploitation of ...

Recent semi-supervised anomaly detection methods that are trained using small labeled anomaly examples and large unlabeled data (mostly normal data) have shown largely improved performance over unsupervised methods. However, these methods often focus on ...

Deep learning promotes the fields of image processing, machine translation and natural language processing etc. It also can be used in network anomaly detection. In practice, it is not hard to obtain normal instances. However, it is always ...