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...Show MoreMetadata
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.
Published in: IEEE Transactions on Neural Networks ( Volume: 20, Issue: 3, March 2009)