Date of Original Version
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Abstract or Description
We present an adaptive graph filtering approach to semi-supervised classification. Adaptive graphfilters 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 theclassification of online blogs and damage identification in indirect bridge structural health monitoring.
Proceedings of the IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2013, 427-430.