Learning to update Auto-associative Memory in Recurrent Neural Networks for Improving Sequence Memorization

19 Sep 2017 Wei Zhang Bo-Wen Zhou

Learning to remember long sequences remains a challenging task for recurrent neural networks. Register memory and attention mechanisms were both proposed to resolve the issue with either high computational cost to retain memory differentiability, or by discounting the RNN representation learning towards encoding shorter local contexts than encouraging long sequence encoding... (read more)

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