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cs.LG2023
Unsupervised Anomaly Detection with Rejection
Lorenzo Perini, Jesse Davis
Anomaly detection aims at detecting unexpected behaviours in the data. Because anomaly detection is usually an unsupervised task, traditional anomaly detectors learn a decision bou…
cs.LG2023★ 1 cited
How to Allocate your Label Budget? Choosing between Active Learning and Learning to Reject in Anomaly Detection
Lorenzo Perini, Daniele Giannuzzi, Jesse Davis
Anomaly detection attempts at finding examples that deviate from the expected behaviour. Usually, anomaly detection is tackled from an unsupervised perspective because anomalous la…