Rotational Unit of Memory: A Novel Representation Unit for RNNs with Scalable Applications
Stacking long short-term memory (LSTM) cells or gated recurrent units (GRUs) as part of a recurrent neural network (RNN) has become a standard approach to solving a number of tasks ranging from language modeling to text summarization. Although LSTMs and GRUs were designed to model long-range depende...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2019-11-01
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| Series: | Transactions of the Association for Computational Linguistics |
| Online Access: | https://www.mitpressjournals.org/doi/abs/10.1162/tacl_a_00258 |