Adaptive graph filtering: Multiresolution classification on graphs

Siheng Chen, Aliaksei Sandryhaila, Jose M.F. Moura, Jelena Kovacevic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present an adaptive graph filtering approach to semi-supervised classification. Adaptive graph filters combine decisions from multiple graph filters using a weighting function that is optimized in a semi-supervised manner. We also demonstrate the multiresolution property of adaptive graph filters by connecting them to the diffusion wavelets. In our experiments, we apply the adaptive graph filters to the classification of online blogs and damage identification in indirect bridge structural health monitoring.

Original languageEnglish (US)
Title of host publication2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
Pages427-430
Number of pages4
DOIs
StatePublished - Dec 1 2013
Event2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Austin, TX, United States
Duration: Dec 3 2013Dec 5 2013

Publication series

Name2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings

Other

Other2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013
CountryUnited States
CityAustin, TX
Period12/3/1312/5/13

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ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

Cite this

Chen, S., Sandryhaila, A., Moura, J. M. F., & Kovacevic, J. (2013). Adaptive graph filtering: Multiresolution classification on graphs. In 2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings (pp. 427-430). [6736906] (2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings). https://doi.org/10.1109/GlobalSIP.2013.6736906