DATA AS DEMONSTRATOR with Applications to System Identification


Machine learning techniques for system identification and time series modeling often phrase the problem as the optimization of a loss function over a single timestep prediction. However, in many applications, the learned model is recursively applied in order to make a multiple-step prediction, resulting in compounding prediction errors. We present DATA AS… (More)


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