… clustering; the overhead (the extra time over the batch algorithm that our anytime algorithm
takes if allowed to … work are: x A novel approximation to Dynamic Time Warping, which is both …

… clustering; and the overhead (the extra time over the batch algorithm that our anytime algorithms
take if allowed to … are: • A novel approximation to Dynamic Time Warping, which is both …

… datasets, as we shall show, the same is not true for clustering… it is critical to allow the clustering
algorithm the freedom to … final clustering, and that if we could find even an approximate …

… a heuristic ordering that gives the anytime algorithm the best … , the anytime clustering
framework and an approximation … As for classified datasets, we apply four objective clustering …

… A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time
Series Datasets. In Proceedings of the 2012 SIAM International Conference on Data Mining…

… , we proposed a novel method to speed-up the calculation of Dynamic Time … A novel
approximation to dynamic time warping allows anytime clustering of massive time series datasets. In …

… This conversion preserves all high amplitude data, while allowing a sparsity … ) A novel
approximation to dynamic time warping allows anytime clustering of massive time series datasets. …

… datasets, as we shall show, the same is not true for clustering. … it is critical to allow the
clustering algorithm the freedom to … final clustering, and that if we could find even an approximate “…

… Section V is about experiments and Section VI provides the … In addition, we compare fDTW
with an approximation to DTW… dynamic time warping measure for multivariate time series …

… is repeated until the “approximation” is the original “raw” data. Our approach allows the user
to … Our work is more similar in spirit to the dynamic time warping similarity search technique …