Stage-Wise Magnitude-Based Pruning for Recurrent Neural Networks

Guiying Li1; Peng Yang2; Chao Qian3; Richang Hong4; Ke Tang1

2022

10.1109/TNNLS.2022.3184730

IEEE Transactions on Neural Networks and Learning Systems   Impact Factor & Quartile

2162-2388

Deep neural network (DNN) compression language models machine translation optimization recurrent neural networks (RNNs)

SCI ; EI

First

20222812350386

Computational linguistics ; Feedforward neural networks ; Job analysis ; Long short-term memory ; Modeling languages ; Natural language processing systems ; Neurons ; Optimization

Ergonomics and Human Factors Engineering:461.4 ; Biology:461.9 ; Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory:721.1 ; Data Processing and Image Processing:723.2 ; Optimization Techniques:921.5

IEEE

1.Research Institute of Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen, China
2.Department of Computer Science and Engineering, Guangdong Key Laboratory of Brain-Inspired Intelligent Computation, Southern University of Science and Technology, Shenzhen, China
3.State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China
4.School of Computer and Information, Hefei University of Technology, Hefei, China

Guiying Li,Peng Yang,Chao Qian,et al. Stage-Wise Magnitude-Based Pruning for Recurrent Neural Networks[J]. IEEE Transactions on Neural Networks and Learning Systems,2022,PP(99):1-15.

Guiying Li,Peng Yang,Chao Qian,Richang Hong,&Ke Tang.(2022).Stage-Wise Magnitude-Based Pruning for Recurrent Neural Networks.IEEE Transactions on Neural Networks and Learning Systems,PP(99),1-15.

Guiying Li,et al."Stage-Wise Magnitude-Based Pruning for Recurrent Neural Networks".IEEE Transactions on Neural Networks and Learning Systems PP.99(2022):1-15.