The University of Chicago on Semi-supervised Kernel Methods a Dissertation Submitted to the Faculty of the Division of the Physical Sciences in Candidacy for the Degree of Doctor of Philosophy Department of Computer Science by Vikas Sindhwani

  • Published 2007
Semi-supervised learning is an emerging computational paradigm for learning from limited supervision by utilizing large amounts of inexpensive, unsupervised observations. Not only does this paradigm carry appeal as a model for natural learning, but it also has an increasing practical need in most if not all applications of machine learning – those where… CONTINUE READING