Lightweight and efficient neural natural language processing with quaternion networks
Many state-of-the-art neural models for NLP are heavily parameterized and thus memory inefficient. This paper proposes a series of lightweight and memory efficient neural architectures for a potpourri of natural language processing (NLP) tasks. To this end, our models exploit computation using Quate...
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Main Authors: | , , , , , , , |
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格式: | text |
語言: | English |
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Institutional Knowledge at Singapore Management University
2019
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在線閱讀: | https://ink.library.smu.edu.sg/scis_studentpub/2 https://ink.library.smu.edu.sg/context/scis_studentpub/article/1002/viewcontent/P19_1145.pdf |
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