Boosting the Convergence of Reinforcement Learning-Based Auto-Pruning Using Historical Data
Author:
Affiliation:
1. Department of Electronics and Communications Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
2. Computing Platform Department, Alibaba Group, Hangzhou, China
Funder
Alibaba Group
RGC GRF
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Software
Link
http://xplorestaging.ieee.org/ielx7/43/10410112/10265172.pdf?arnumber=10265172
Reference39 articles.
1. Learning both weights and connections for efficient neural network;Han
2. Channel Pruning for Accelerating Very Deep Neural Networks
3. Discrimination-aware channel pruning for deep neural networks;Zhuang
4. An entropy-based pruning method for CNN compression;Luo;arXiv:1706.05791,2017
5. Learning sparse neural networks through L0 regularization;Louizos;arXiv:1712.01312,2017
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