Identifying anomalies in time series data can be daunting, thanks to the vague definition of anomalies, lack of labelled data, and highly complex temporal correlations. Currently, the machine learning method used for anomaly detection faces scalability and portability issues, resulting in false-positives. And, therein lies the problem. In a recent paper, MIT researchers proposed an…

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