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R. Kiran (Univ. Lille 3): Streaming multi-scale anomaly detection for univariate time series

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In this talk we motivate the use of a multi-scale embedding of time series to localize anomalies in the given time series, in a online streaming setup. The reconstruction error produced by the projection of the new incoming window on to the principal component at each scale serves as the anomaly score for a given scale or window size. The aggregation of errors from multiple scales into a final anomaly score is also explored. The method was evaluated on the Yahoo! and Numenta datasets for streaming anomaly detection.

Thursday, May 4, 2017 - 11:00 to 12:00
Inria B21
Ravi Kiran
Université Lille 3