Semi-supervised support vector machines
Proceedings of the 1998 conference on Advances in neural information processing systems II
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
The Journal of Machine Learning Research
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One of the central problems in machine learning is how to effectively combine unlabelled and labelled data to infer the labels of unlabelled ones. In recent years, there has a growing interest on the transduction method. In this article, the transductive learning machines are described based on a so-called affinity rule which comes from the intuitive fact that if two objects are close in input space then their outputs should also be close, to obtain the solution of semi-supervised learning problem. By using the analytic solution for this problem, an incremental learning algorithm adapting to on-line data processing is derived.