Simplified Gating in Long Short-term Memory (LSTM) Recurrent Neural Networks

12 Jan 2017Yuzhen LuFathi M. Salem

The standard LSTM recurrent neural networks while very powerful in long-range dependency sequence applications have highly complex structure and relatively large (adaptive) parameters. In this work, we present empirical comparison between the standard LSTM recurrent neural network architecture and three new parameter-reduced variants obtained by eliminating combinations of the input signal, bias, and hidden unit signals from individual gating signals... (read more)

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