Dynamic Subspace Update with Incremental Nyström Approximation

  • Hongyu Li
  • Lin Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6469)


Low rank approximation methods, e.g. the Nyström method, are often used to speed up eigen-decomposition of kernel matrices. However, it cannot effectively update the extracted subspaces when datasets dynamically increase with time. In this paper, we propose an incremental Nyström method for dynamic learning. Experimental results demonstrate the feasibility and effectiveness of the proposed method.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Hongyu Li
    • 1
  • Lin Zhang
    • 1
  1. 1.School of Software EngineeringTongji UniversityShanghaiChina

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