Nonlinear System Identification via Tensor Completion

13 Jun 2019Nikos KargasNicholas D. Sidiropoulos

Function approximation from input and output data pairs constitutes a fundamental problem in supervised learning. Deep neural networks are currently the most popular method for learning to mimic the input-output relationship of a general nonlinear system, as they have proven to be very effective in approximating complex highly nonlinear functions... (read more)

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