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: TAY, Yi, ZHANG, Aston, LUU, Anh Tuan, RAO, Jinfeng, ZHANG, Shuai, WANG, Shuohang, FU, Jie, HUI, Siu Cheung
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2019
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Online Access: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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Institution: Singapore Management University
Language: English