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Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews]

IEEE Transactions on Neural Networks · 2009 · Vol. 20(3) · pp. 542–542
Olivier ChapelleBernhard SchölkopfEds. A. Zien

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.

Experimental Learning in EngineeringAdvanced Control Systems OptimizationAdvanced Control Systems DesignComputer scienceGraphArtificial intelligenceGenerative grammarMachine learningTheoretical computer science
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