Recurrent Neural Networks With Auxiliary Memory Units.
IEEE Transactions on Neural Networks and Learning Systems(2018)
摘要
Memory is one of the most important mechanisms in recurrent neural networks (RNNs) learning. It plays a crucial role in practical applications, such as sequence learning. With a good memory mechanism, long term history can be fused with current information, and can thus improve RNNs learning. Developing a suitable memory mechanism is always desirable in the field of RNNs. This paper proposes a nov...
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关键词
Neurons,Logic gates,Recurrent neural networks,Computer architecture,Microprocessors,Biological neural networks,Convergence
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