• DocumentCode
    257888
  • Title

    Graph signal coarsening: Dimensionality reduction in irregular domain

  • Author

    Pengfei Liu ; Xiaohan Wang ; Yuantao Gu

  • Author_Institution
    Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
  • fYear
    2014
  • fDate
    3-5 Dec. 2014
  • Firstpage
    798
  • Lastpage
    802
  • Abstract
    Graph signal coarsening is a kind of dimensionality reduction in irregular domain. Given a graph signal, it aims to simultaneously obtain a coarser version of the graph and a coarsened signal on the new graph. In this work, we explore the design space for the graph signal coarsening problem and show that solutions can be split into four categories. We propose an effective method that uses a successive approach and spectral-domain-based signal coarsening for solving the problem, which is the first that falls into one of the four categories. Experiments are conducted to show the effectiveness of the proposed method.
  • Keywords
    graph theory; signal processing; dimensionality reduction; graph signal coarsening problem; irregular domain; spectral-domain-based signal coarsening; Approximation algorithms; Communities; Eigenvalues and eigenfunctions; Laplace equations; Space exploration; Spectral analysis; dimensionality reduction; graph signal coarsening; graph signal processing; irregular domain; spectral graph theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing (GlobalSIP), 2014 IEEE Global Conference on
  • Conference_Location
    Atlanta, GA
  • Type

    conf

  • DOI
    10.1109/GlobalSIP.2014.7032229
  • Filename
    7032229