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Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews]
Abstract
This book addresses some theoretical aspects of semisupervised learning (SSL). The book is organized as a collection of different contributions of authors who are experts on this topic. The objectives of this book are to present a large overview of the SSL methods and to classify these methods into four classes that correspond to the first four main parts of the book (this would include generative models; low-density separation methods; graph-based methods; and algorithms). The last two parts are devoted to applications and perspectives of SSL. The book responds to its major objectives and could serve as a basis for an intermediate level graduate course on SSL. It may also serve as a useful self study and reference source for practicing engineers.
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Citations
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Metadata
- Authors
- Chapelle, O., Scholkopf, B., & Zien, E.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 2009-03
- Volume
- 20
- Issue
- 3
- Pages
- 542-542
- ISSN
- 1045-9227 (ISSN-L)
- OpenAlex
- W1983320747
- Cited by
- 1,066
- References
- 0
- Type
- book review
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
