Academic Press Library in Signal Processing

Chapter 22

Semi-Supervised Learning

Xueyuan Zhou* and Mikhail Belkin^†,    ^*Department of Computer Science, The University of Chicago, 1100 East 58th Street, Chicago, IL, USA,    ^†Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA, [e-mail], [e-mail]

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 ...