PP: Soft-DTW: a differentiable loss function for time-series
Problem: new loss
Label: new loss;
Abstract:
A differentiable learning loss;
Introduction:
supervised learning: learn a mapping that links an input to an output object.
output object is a time series.
Prediction: two multi-layer perceptrons, the first use Euclidean loss and the second use soft-DTW as a loss function. --------> soft-DTW, better sharp changes.
DTW computes the best possible alignment between two time series.
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