Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data

T1Covered by 1 source · first reported by arXiv at 25 Sept, 04:00 UTC

arXiv:2405.18929v3 Announce Type: replace-cross Abstract: Semi-supervised anomaly detection, which aims to improve the anomaly detection performance by using a small amount of labeled anomaly data in addition to unlabeled data, has attracted attention. Existing semi-supervised approaches assume…

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Sources

• T1Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled DataarXiv25 Sept, 04:00