Discovering Multivariate Motifs using Subsequence Density Estimation and Greedy Mixture Learning Abstract The problem of locating motifs in real-valued, multivariate time series data involves the discovery of sets of recurring patterns embedded in the time series. Each set is composed of several non-overlapping subsequences and constitutes a motif because all of the included subsequences are […]