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A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis
The continued digitization of societal processes translates into a proliferation of time series data that cover applications such as fraud detection, intrusion detection, and energy management, where anomaly detection is often essential to enable reliability and safety.
HIFI: Anomaly Detection for Multivariate Time Series with High-order Feature Interactions
Monitoring complex systems results in massive multivariate time series data, and anomaly detection of these data is very important to maintain the normal operation of the systems.
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