Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 8
2371-2375

Unsupervised domain adaptive algorithm with intra-class maximum mean discrepancy

Cai Ruichu1
Li Jiahao1
Hao Zhifeng1,2
1. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
2. College of Mathematics & Big Data, Foshan University, Foshan Guangdong 528225, China
DOI: 10.19734/j.issn.1001-3695.2019.03.0042

Abstract

In the unsupervised domain adaptation area, loss of label information is still an open problem during the alignment of the global distribution, and thus the effect of transfer learning is difficult to guarantee. To alleviate this problem, this paper proposed an algorithm which adopted a distribution alignment strategy based on the intra-class maximum mean discrepancy. This strategy firstly predicted the pseudo labels for all samples, then aligned the intra-class distributions of two domains with the help of the predicted labels. Under the deep learning framework, the proposed algorithm effectively avoided label information being washed away and greatly improved the prediction ability on the target domain. The experimental results show that the proposed algorithm outperforms the traditional algorithms on the benchmarks.

Foundation Support

NSFC—广东联合基金资助项目(U1501254)
国家自然科学基金资助项目(61876043,61472089)
广东省自然科学基金资助项目(2014A030306004,2014A030308008)
广东省科技计划资助项目(2015B010108006,2015B010131015)
广东特支计划资助项目(2015TQ01X140)
广州市珠江科技新星项目(201610010101)
广州市科技计划资助项目(201604016075)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.03.0042
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 8
Section: Algorithm Research & Explore
Pages: 2371-2375
Serial Number: 1001-3695(2020)08-027-2371-05

Publish History

[2020-08-05] Printed Article

Cite This Article

蔡瑞初, 李嘉豪, 郝志峰. 基于类内最大均值差异的无监督领域自适应算法 [J]. 计算机应用研究, 2020, 37 (8): 2371-2375. (Cai Ruichu, Li Jiahao, Hao Zhifeng. Unsupervised domain adaptive algorithm with intra-class maximum mean discrepancy [J]. Application Research of Computers, 2020, 37 (8): 2371-2375. )

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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