Recurrent Neural Networks With Auxiliary Memory Units
Volume: 29, Issue: 5, Pages: 1652 - 1661
Published: May 1, 2018
Abstract
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 novel memory mechanism for RNNs. The main...
Paper Details
Title
Recurrent Neural Networks With Auxiliary Memory Units
Published Date
May 1, 2018
Volume
29
Issue
5
Pages
1652 - 1661
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