DAD detects multivariate time-series anomalies by measuring the change in an online-learned decorrelation matrix, achieving the best mean AUC (0.8027) among 15 methods on 50 datasets.
Unsupervised anomaly detection algorithms on real-world data: how many do we need?,
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Real-Time Decorrelation-Based Anomaly Detection for Multivariate Time Series
DAD detects multivariate time-series anomalies by measuring the change in an online-learned decorrelation matrix, achieving the best mean AUC (0.8027) among 15 methods on 50 datasets.