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Adaptive graph nonnegative matrix factorization with the self-paced regularization

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Abstract

Nonnegative matrix factorization (NMF) is a popular approach to extract intrinsic features from the original data. As the nonconvexity of NMF formulation, it always leads to degrade the performance. To alleviate the defect, in this paper, the self-paced regularization is introduced to find a better factorized matrices by sequentially selecteing data in the learning process. Additionally, to find the low-dimensional manifold embeded in the high-dimensional space, adaptive graph is introduced by using dynamic neighbors assignment. An alternating iterative algorithm is designed to sovle the proposed mathematical factorization formulation. The experimental results are given to show the effectiveness of the proposed approach in comparison with state-of-the-art algorithms on six public datasets.

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Notes

  1. http://archive.ics.uci.edu/ml/datasets/Estimation+of+obesity+levels+based+on+eating+habits+and+physical+condition+http://archive.ics.uci.edu/ml/datasets/Estimation+of+obesity+levels+based+on+eating+habits+and+physical+condition+

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

  3. http://archive.ics.uci.edu/ml/datasets/HCV+data

  4. http://archive.ics.uci.edu/ml/datasets/Heart+failure+clinical+records

  5. https://www.visioneng.org.uk/datasets/

  6. http://archive.ics.uci.edu/ml/datasets/Early+stage+diabetes+ris+prediction+dataset.

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Acknowledgements

This work is supported by the Fundamental Research Funds for the Central Universities (Grant No.SWU020006), National Natural Science Foundation of China(Grant No. 62003281), Natural Science Foundation of Chongqing, China (Grant No. cstc2021jcyj-msxmX1169).

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Authors and Affiliations

  1. College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China

    Xuanhao Yang & Hangjun Che

  2. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Chongqing, 400715, China

    Hangjun Che

  3. School of Computing and Information Science, Faculty of Science and Engineering, Anglia Ruskin University, Cambridge, UK

    Man-Fai Leung

  4. Department of Computer Science, Shantou University, Shantou, China

    Cheng Liu

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  1. Xuanhao Yang
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  4. Cheng Liu
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Correspondence to Hangjun Che.

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Yang, X., Che, H., Leung, MF. et al. Adaptive graph nonnegative matrix factorization with the self-paced regularization. Appl Intell 53, 15818–15835 (2023). https://doi.org/10.1007/s10489-022-04339-w

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