Toward deep supervised anomaly detection: Reinforcement learning from partially labeled anomaly data

• Main Authors: PANG, Guansong, HENGEL, Anton Van Den, SHEN, Chunhua, CAO, Longbing
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Anomaly Detection; Deep Learning; Reinforcement Learning; Neural Networks; Outlier Detection; Intrusion Detection; Artificial Intelligence and Robotics; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/7055; https://ink.library.smu.edu.sg/context/sis_research/article/8058/viewcontent/3447548.3467417.pdf
• Institution: Singapore Management University

We consider the problem of anomaly detection with a small set of partially labeled anomaly examples and a large-scale unlabeled dataset. This is a common scenario in many important applications. Existing related methods either exclusively fit the limited anomaly examples that typically do not span t...