Algorithm Research & Explore
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1463-1467

Neural network hybrid compression method based on information bottleneck

Zhuo Yue
Jiang Li
Dept. of Microelectron Science & Engineering, Xiangtan University, Xiangtan Hunan 411100, China

Abstract

How to deploy neural networks in mobile or embedded devices with limited computing and storage capabilities is a problem that must be faced in the development of neural networks. In order to compress the model size and reduce the computational pressure, this paper proposed a neural network hybrid compression scheme based on the information bottleneck. Based on the information bottleneck, this scheme found redundant information between adjacent neural network layers and used this as a basis to trim redundant neurons, then performed ternary quantization on the remaining neurons to further reduce the model storage memory. The experimental results show that compared with similar algorithms on the MNIST and CIFAR-10 datasets, the proposed method has higher compression rate and lower calculation amount.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.01.0009
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 5
Section: Algorithm Research & Explore
Pages: 1463-1467
Serial Number: 1001-3695(2021)05-033-1463-05

Publish History

[2021-05-05] Printed Article

Cite This Article

卓越, 姜黎. 一种基于信息瓶颈的神经网络混合压缩方法 [J]. 计算机应用研究, 2021, 38 (5): 1463-1467. (Zhuo Yue, Jiang Li. Neural network hybrid compression method based on information bottleneck [J]. Application Research of Computers, 2021, 38 (5): 1463-1467. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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