On the Choice of Kernel and Labelled Data in Semi-supervised Learning Methods

@inproceedings{Avrachenkov2013OnTC,
  title={On the Choice of Kernel and Labelled Data in Semi-supervised Learning Methods},
  author={Konstantin Avrachenkov and Paulo Gonçalves and Marina Sokol},
  booktitle={WAW},
  year={2013}
}
Semi-supervised learning methods constitute a category of machine learning methods which use labelled points together with unlabelled data to tune the classifier. The main idea of the semi-supervised methods is based on an assumption that the classification function should change smoothly over a similarity graph, which represents relations among data points… CONTINUE READING