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A More Efficient and Practical Modified Nyström Method

Author

Listed:
  • Wei Zhang

    (Fair Friend Institute of Intelligent Manufacturing, Hangzhou Vocational & Technical College, Hangzhou 310018, China)

  • Zhe Sun

    (Post Industry Technology Research and Development Center of the State Posts Bureau (Internet of Things Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China
    Post Big Data Technology and Application Engineering Research Center of Jiangsu Province, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)

  • Jian Liu

    (College of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China)

  • Suisheng Chen

    (Fair Friend Institute of Intelligent Manufacturing, Hangzhou Vocational & Technical College, Hangzhou 310018, China)

Abstract

In this paper, we propose an efficient Nyström method with theoretical and empirical guarantees. In parallel computing environments and for sparse input kernel matrices, our algorithm can have computation efficiency comparable to the conventional Nyström method, theoretically. Additionally, we derive an important theoretical result with a compacter sketching matrix and faster speed, at the cost of some accuracy loss compared to the existing state-of-the-art results. Faster randomized SVD and more efficient adaptive sampling methods are also proposed, which have wide application in many machine-learning and data-mining tasks.

Suggested Citation

  • Wei Zhang & Zhe Sun & Jian Liu & Suisheng Chen, 2023. "A More Efficient and Practical Modified Nyström Method," Mathematics, MDPI, vol. 11(11), pages 1-13, May.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2433-:d:1154942
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