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A Modified Semi-Supervised Learning Algorithm on Laplacian Eigenmaps

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Abstract

In this letter, a modified algorithm is proposed to extend 2-class semi-supervised learning on Laplacian eigenmaps to multi-class learning problems. The modified algorithm significantly increases its learning speed, and at the same time attains a satisfactory classification performance that is not lower than the original algorithm.

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Authors and Affiliations

  1. College of Computer Science and Information Engineering, Hefei University of Technology, Hefei, 230009, China

    Zhong-Qiu Zhao, Jun-Zhao Li, Jun Gao & Xindong Wu

  2. Department of Computer Science, University of Vermont, Burlington, VT, USA

    Xindong Wu

Authors
  1. Zhong-Qiu Zhao
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  2. Jun-Zhao Li
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  3. Jun Gao
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  4. Xindong Wu
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Corresponding author

Correspondence to Zhong-Qiu Zhao.

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Zhao, ZQ., Li, JZ., Gao, J. et al. A Modified Semi-Supervised Learning Algorithm on Laplacian Eigenmaps. Neural Process Lett 32, 75–82 (2010). https://doi.org/10.1007/s11063-010-9142-0

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  • DOI: https://doi.org/10.1007/s11063-010-9142-0

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