Manifold Regularization

In this lecture we introduce a class of learning algorithms, collectively called manifold regularization algorithms, suited for predicting/classifying data embedded in high-dimensional spaces. We introduce manifold regularization in the framework of semi-supervised learning, a generalization of the supervised learning setting in which our training set may consist of unlabeled as well as labeled examples.