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Graph-based methods play an important role in unsupervised andsemi-supervised learning tasks by taking into account the underlying geometryof the data set. In this paper, we consider a statistical setting forsemi-supervised learning and provide a formal justification of the recentlyintroduced framework of bandlimited interpolation of graph signals. Ouranalysis leads to the interpretation that, given enough labeled data, thismethod is very closely related to a constrained low density separation problemas the number of data points tends to infinity. We demonstrate the practicalutility of our results through simple experiments.

Asymptotic Justification of Bandlimited Interpolation of Graph signals for Semi-Supervised Learning