Rotational Unit of Memory: A Novel Representation Unit for RNNs with Scalable Applications
<jats:p> 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 lon...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
MIT Press - Journals
2022
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| Online Access: | https://hdl.handle.net/1721.1/132374.2 |