A Weakly Supervised Learning Approach based on Spectral Graph-Theoretic Grouping

arXiv: Learning, (2015)

Cited by: 1|Views11
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Abstract:

In this study, a spectral graph-theoretic grouping strategy for weakly supervised classification is introduced, where a limited number of labelled samples and a larger set of unlabelled samples are used to construct a larger annotated training set composed of strongly labelled and weakly labelled samples. The inherent relationship between...More

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