arXiv stat.ML
· Papers
Early Failure Prediction from Near-Anomaly Detection: A Proactive Approach
arXiv:2607.26704v1 Announce Type: new Abstract: Anomaly detection methods often have uncertain behavior with respect to samples near the distribution boundary, limiting their ability to anticipate future anomalies. This work introduces the concept of near-anomalies that, while not yet anomalous, lie close to the bounda