Kernel-based transition probability toward similarity measure for semi-supervised learning

Abstract

For improving the classification performance on the cheap, it is necessary to exploit both labeled and unlabeled samples by applying semi-supervised learning methods, most of which are built upon the pairwise similarities between the samples. While the similarities have so far been formulated in a heuristic manner such as by k-NN, we propose methods to… (More)
DOI: 10.1016/j.patcog.2013.11.011

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