Speedup from a different parametrization within the Neural Network algorithm

20 May 2017 Michael F. Zimmer

A different parametrization of the hyperplanes is used in the neural network algorithm. As demonstrated on several autoencoder examples it significantly outperforms the usual parametrization, reaching lower training error values with only a fraction of the number of epochs... (read more)

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