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Semi-supervised learning

Author: Olivier Chapelle; Bernhard Schölkopf; Alexander Zien
Publisher: Cambridge, Mass. : MIT Press, ©2006.
Series: Adaptive computation and machine learning.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems: state-of-the-art algorithms, a taxonomy of the field, applications,  Read more...

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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Olivier Chapelle; Bernhard Schölkopf; Alexander Zien
ISBN: 0262033585 9780262033589 9780262033589
OCLC Number: 64898359
Description: x, 508 pages : illustrations ; 26 cm.
Contents: 1. Introduction to semi-supervised learning --
2. A taxonomy for semi-supervised learning methods / Matthias Seeger --
3. Semi-supervised text classification using EM / Kamal Nigam, Andrew McCallum and Tom Mitchell --
4. Risks of semi-supervised learning / Fabio Cozman and Ira Cohen --
5. Probabilistic semi-supervised clustering with constraints / Sugato Basu, Mikhail Bilenko, Arindam Benerjee and Raymond Mooney --
6. Transductive support vector machines / Thorsten Joachims --
7. Semi-supervised learning using semi-definite programming / Tijl De Bie and Nello Cristianini --
8. Gaussian processes and the null-category noise model / Neil D. Lawrence and Michael I. Jordan --
9. Entropy regularization / Yves Grandvalet and Yoshua Bengio --
10. Data-dependent regularization / Adrian Corduneanu and Tommi Jaakkola --
11. Label propagation and quadratic criterion / Yoshua Bengio, Olivier Delalleau and Nicolas Le Roux --
12. The geometric basis of semi-supervised learning / Vikas Sindhwani, Misha Belkin and Partha Niyogi --
13. Discrete regularization / Dengyong Zhou and Bernhard Scholkopf --
14. Semi-supervised learning with conditional harmonic mixing / Christopher J.C. Burges and John C. Platt --
15. Graph kernels by spectral transforms / Xiaojin Zhu, Jaz Kandola, John Lafferty and Zoubin Ghahramani --
16. Spectral methods for dimensionality reduction / Lawrence K. Saul, Kilian Q. Weinberger, Fei Sha, Jihun Ham and Daniel D. Lee --
17. Modifying distances / Sajama and Alon Orlitsky --
18. Large-scale algorithms / Olivier Delalleau, Yoshua Bengio and Nicolas Le Roux --
19. Semi-supervised protein classification using cluster kernels / Jason Westton, Christina Leslie, Eugene Ie and William Stafford Noble --
20. Prediction of protein function from networks / Hyunjung Shin and Koji Tsuda --
21. Analysis of benchmarks --
22. An augmented PAC model for semi-supervised learning / Maria-Florina Balcan and Avrim Blum --
23. Metric-based approaches for semi-supervised regression and classification / Dale Schuuramans, Finnegan Southey, Dana Wilkinson and Yuhong Guo --
24. Transductive inference and semi-supervised learning / Vladimir Vapnik --
25. A discussion of semi-supervised learning and transduction.
Series Title: Adaptive computation and machine learning.
Responsibility: [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien.

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In summary, reading this book is a delightful journey through semi-supervised learning. -- Hsun-Hsien Chang * Computing Reviews *

 
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