Soft-DTW: a Differentiable Loss Function for Time-Series

ICML 2017 Marco CuturiMathieu Blondel

We propose in this paper a differentiable learning loss between time series, building upon the celebrated dynamic time warping (DTW) discrepancy. Unlike the Euclidean distance, DTW can compare time series of variable size and is robust to shifts or dilatations across the time dimension... (read more)

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