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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 2
485-490

Feature learning method based on improved graph regularized auto-encoder

Wu Wenbin
Zhou Wei
Tang Dongming
School of Computer Science & Engineering, Southwest Minzu University, Chengdu 610041, China
DOI: 10.19734/j.issn.1001-3695.2021.06.0223

Abstract

Traditional graph regularization methods use Euclidean distance to measure the similarity of sample space, and can not accurately preserve the neighborhood information of complex data sets, which easily lead to the degradation of the generalization performance of the model in complex shape data and non convex data sets. This paper proposed an improved graph regularization algorithm, which used isometric feature mapping to preserve the neighborhood information of the sample space and help the model learn manifold. The simultaneous used of KL constraints further smoothed the external structure of the data representation, thereby capturing more sparse and advanced feature representations. Experimental results on MNIST and YaleB datasets show that compared with several popular feature extraction algorithms, the proposed algorithm can extract more mea-ningful and robust features. It has advantages in classification and clustering tasks, and also has better anti-interference capability.

Foundation Support

四川省科技计划资助项目(2019YFG0207)
西南民族大学2021年研究生“创新型科研项目”(CX2021SZ51)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.06.0223
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 2
Section: Algorithm Research & Explore
Pages: 485-490
Serial Number: 1001-3695(2022)02-027-0485-06

Publish History

[2021-10-08] Accepted Paper
[2022-02-05] Printed Article

Cite This Article

吴文彬, 周伟, 唐东明. 基于改进图正则项的自编码器特征学习算法 [J]. 计算机应用研究, 2022, 39 (2): 485-490. (Wu Wenbin, Zhou Wei, Tang Dongming. Feature learning method based on improved graph regularized auto-encoder [J]. Application Research of Computers, 2022, 39 (2): 485-490. )

About the Journal

  • 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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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