Pseudo-density Estimation for Clustering with Gaussian Processes

  • Hyun-Chul Kim
  • Jaewook Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)


Gaussian processes (GP) provide a kernel machine framework. They have been mainly applied to regression and classification. We propose a pseudo-density estimation method based on the information of variance functions of GPs, which relates to the density of the data points. We also show how the constructed pseudo-density can be applied to clustering. Through simulation we show that the topology of the pseudo-density represents the clustering information well with promising results.


Gaussian Process Sample Function Gaussian Process Regression Gaussian Process Model Kernel Machine 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hyun-Chul Kim
    • 1
  • Jaewook Lee
    • 1
  1. 1.Department of Industrial and Management EngineeringPohang University of Science and TechnologyPohang, KyungbukKorea

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