JumpStarter is a comprehensive multivariate time series anomaly detection approach based on **Compressed Sensing** (CS). CS is a signal processing technique where high-energy components in a matrix (multivariate time series) are sparse (i.e. have few high-energy components).
Hence, the difference between the original and the reconstructed multivariate time series, comprised only of low-energy components, should resemble white noise, when the original time series contains no anomaly.
