Towards Energy-Preserving Natural Language Understanding With Spiking Neural Networks
Author:
Affiliation:
1. Damo Academy, Alibaba Group, Hangzhou, China
2. NLP CT Lab, University of Macau, Macao, China
3. Zhejiang University, Hangzhou, China
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
China Postdoctoral Science Foundation
Science and Technology Development Fund, Macau SAR
Multi-year Research Grant from the University of Macau
Alibaba Group
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics
Link
http://xplorestaging.ieee.org/ielx7/6570655/9970249/09944911.pdf?arnumber=9944911
Reference39 articles.
1. Unsupervised Cross-lingual Representation Learning at Scale
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4. DIET-SNN: Direct input encoding with leakage and threshold optimization in deep spiking neural networks;rathi,2020
5. H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks
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