A Survey on Deep Semi-Supervised Learning

A Survey on Inductive Semi-supervised Learning

A Survey on Semi-Supervised Learning Techniques

Semi-supervised learning is a learning standard which deals with the study of how computers and natural systems such as human beings acquire knowledge in the presence of both labeled and unlabeled data. Semi–supervised learning based methods are preferred when compared to the supervised and unsupervised learning because of the improved performance shown by the semi-supervised approaches in the ...

Semi-supervised deep kernel learning

Deep learning techniques have led to massive improvements in recent years, but large amounts of labeled data are typically required to learn these complex models. We present a semi-supervised approach for training deep models that combines the feature learning capabilities of neural networks with the probabilistic modeling of Gaussian processes and demonstrate that unlabeled data can significan...

Semi-Supervised Learning Literature Survey

Semi-supervised Learning with Deep Generative Models

The ever-increasing size of modern data sets combined with the difficulty of obtaining label information has made semi-supervised learning one of the problems of significant practical importance in modern data analysis. We revisit the approach to semi-supervised learning with generative models and develop new models that allow for effective generalisation from small labelled data sets to large ...