Towards safe and robust weakly-supervised anomaly detection under subpopulation shift

Rundong He; Zhongyi Han; Yilong Yin

doi:10.1016/j.knosys.2022.109088

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JOURNAL ARTICLE

Towards safe and robust weakly-supervised anomaly detection under subpopulation shift

Rundong He Zhongyi Han Yilong Yin

Year: 2022 Journal: Knowledge-Based Systems Vol: 250 Pages: 109088-109088 Publisher: Elsevier BV

DOI: 10.1016/j.knosys.2022.109088

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Keywords:

Anomaly detection Computer science Statistic Estimator Anomaly (physics) Intersection (aeronautics) Data mining Construct (python library) Pattern recognition (psychology) Artificial intelligence Mathematics Statistics Engineering

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Data-Driven Disease Surveillance

Health Sciences → Medicine → Epidemiology

Towards safe and robust weakly-supervised anomaly detection under subpopulation shift

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