Laplacian embedded regression for scalable manifold regularization
Semi-supervised learning (SSL), as a powerful tool to learn from a limited number of labeled data and a large number of unlabeled data, has been attracting increasing attention in the machine learning community. In particular, the manifold regularization framework has laid solid theoretical foundati...
Main Authors: | , , |
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Other Authors: | |
Format: | Journal Article |
Language: | English |
Published: |
2013
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/99250 http://hdl.handle.net/10220/13482 |