Elements of generative manifold learning for semi-supervised tasks

摘要: For many real-world application problems, the availability of data labels for supervised learning is rather limited. It often case that a limited number labelled cases accompanied by larger unlabeled ones. This setting semi-supervised learning, in which unsupervised approaches assist problem and viceversa. In this report, we outline some basic theoretical foundations using models generative manifold-learning family.