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	Chapelle, Olivier     Options: All Media Types Journals Proceedings Div Books Whole Books Other Date Reviewed Title Author Publisher Published Date Descending Ascending Date Reviewed     1 - 4 of 4 reviews       Semi-supervised learning Chapelle O., Schölkopf B., Zien A., The MIT Press, Cambridge, MA, 2010. 528 pp.  Type: Book (978-0-262514-12-5) Semi-supervised learning is an emerging area that stands between supervised learning and unsupervised learning. Supervised learning requires all data be labeled in order to learn a model, while unsupervised learning needs no labeled da...... Feb 14 2011     Large-scale kernel machines (Neural Information Processing) Bottou L., Chapelle O., DeCoste D., Weston J., The MIT Press, 2007. 416 pp.  Type: Book (9780262026253) Kernel-based techniques represent a major development in machine learning algorithms. These techniques include support vector machines (SVM), Bayes point machines, kernel principal component analysis, and Gaussian processes. SVMs are a...... Apr 10 2008     Training a support vector machine in the primal Chapelle O. Neural Computation 19(5): 1155-1178, 2007.  Type: Article Support vector machines (SVMs) are a novel and powerful technique for classification. In order to obtain the optimal classification, one needs to solve the primal or dual problem. Usually, the primal problem is a quadratic optimization...... Sep 27 2007     Semi-supervised learning Chapelle O., Schölkopf B., Zien A., The MIT Press, 2006.  Type: Book (9780262033589) It seems that the answer to the old question of whether mixing labeled and unlabeled data can produce better models in machine learning is converging to a definite “yes.” However, the assumptions, conditions...... Jul 20 2007
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