Autoencoder-based Initialization for Recurrent Neural Networks with a Linear Memory

ICLR 2020 Anonymous

Orthogonal recurrent neural networks address the vanishing gradient problem by parameterizing the recurrent connections using an orthogonal matrix. This class of models is particularly effective to solve tasks that require the memorization of long sequences... (read more)

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