Adaptive graph filtering: Multiresolution classification on graphs

TL;DR: In this work, an adaptive graph filtering approach to semi-supervised classification is presented and the multiresolution property of adaptive graph filters is demonstrated by connecting them to the diffusion wavelets.

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.