Abstract: In the world of modern technology, digital data are generated at a lightning speed. These data are typically unlabeled as obtaining labels often requires time-consuming and costly human input. Semi-supervised learning was introduced to study the problem of using the labeled and unlabeled data together to improve learning. Two basic questions of semi-supervised learning are understanding the usefulness of unlabeled data for learning and of designing effective algorithms for using unlabeled data. In this chapter we discuss the principles of semi-supervised learning and several popular classes of algorithms.
Publication Year: 2014
Publication Date: 2014-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 97
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