6 citations · 13 across the 5 of their papers we have counts for
4 papers · 1 filter
Slim LSTM networks: LSTM_6 and LSTM_C6
Atra Akandeh, Fathi M. Salem
We have shown previously that our parameter-reduced variants of Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNN) are comparable in performance to the standard LSTM RNN…
Simplified Long Short-term Memory Recurrent Neural Networks: part III
Atra Akandeh, Fathi M. Salem
This is part III of three-part work. In parts I and II, we have presented eight variants for simplified Long Short Term Memory (LSTM) recurrent neural networks (RNNs). It is noted…
Simplified Long Short-term Memory Recurrent Neural Networks: part II
Atra Akandeh, Fathi M. Salem
This is part II of three-part work. Here, we present a second set of inter-related five variants of simplified Long Short-term Memory (LSTM) recurrent neural networks by further re…
Simplified Long Short-term Memory Recurrent Neural Networks: part I
Atra Akandeh, Fathi M. Salem
We present five variants of the standard Long Short-term Memory (LSTM) recurrent neural networks by uniformly reducing blocks of adaptive parameters in the gating mechanisms. For s…