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Pacific Rim Conference on Multimedia

PCM 2017: Advances in Multimedia Information Processing – PCM 2017 pp 526–533Cite as

Least-Squares Regulation Based Graph Embedding

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10735))

Abstract

A large family of algorithms named graph embedding is widely accepted as an effective technique designed to provide better solutions to the problem of dimensionality reduction. Existing graph embedding algorithms mainly consider obtaining projection directions through preserving local geometrical structure of data. In this paper, a regulation formulation known as Least-Squares Reconstruction Errors, to unify various graph embedding methods within a common regulation framework for preserving both local and global structures, is proposed. With its properties of Least-Squares regulation, orthogonality constraint to data distributions and tensor extensions of supervised or semi-supervised scenarios, this common regulation framework makes a tradeoff between intrinsic geometrical structure and the global structure. Our experiments demonstrated that, our proposed method have better performances in keeping lower dimensional subspaces and higher classification results.

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Notes

  1. 1.

    http://www.cad.zju.edu.cn/home/dengcai/Data/MLData.html.

  2. 2.

    http://www.cs.nyu.edu/~roweis/data.html.

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Acknowledgments

This work was funded in part by the National Natural Science Foundation of China (No. 61572240), and the Open Project Program of the National Laboratory of Pattern Recognition (NLPR) (No. 201600005).

Author information

Authors and Affiliations

  1. School of Computer Science and Telecommunication Engineering, Jiangsu University, Zhenjiang, China

    Si-Xing Liu, Timothy Apasiba Abeo & Xiang-Jun Shen

  2. Tamale Technical University, Box 3ER, Tamale, Ghana

    Timothy Apasiba Abeo

Authors
  1. Si-Xing Liu
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  2. Timothy Apasiba Abeo
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  3. Xiang-Jun Shen
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Corresponding author

Correspondence to Si-Xing Liu .

Editor information

Editors and Affiliations

  1. University of Electronic Science and Technology of China, Chengdu, China

    Bing Zeng

  2. University of Chinese Academy of Sciences, Beijing, China

    Qingming Huang

  3. University of Ottawa, Ottawa, Ontario, Canada

    Abdulmotaleb El Saddik

  4. University of Electronic Science and Technology of China, Chengdu, China

    Hongliang Li

  5. Chinese Academy of Sciences, Beijing, China

    Shuqiang Jiang

  6. Harbin Institute of Technology, Harbin, China

    Xiaopeng Fan

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Liu, SX., Abeo, T.A., Shen, XJ. (2018). Least-Squares Regulation Based Graph Embedding. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10735. Springer, Cham. https://doi.org/10.1007/978-3-319-77380-3_50

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  • DOI: https://doi.org/10.1007/978-3-319-77380-3_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77379-7

  • Online ISBN: 978-3-319-77380-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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