Abstract. This article presents a unified theory for analysis of components in discrete data, and compares the methods with techniques such as independent component analysis, non-...
Post-nonlinear (PNL) independent component analysis (ICA) is a generalisation of ICA where the observations are assumed to have been generated from independent sources by linear mi...
Relevant component analysis (RCA) is a recently proposed metric learning method for semi-supervised learning applications. It is a simple and efficient method that has been applie...
: Semantic clustering is important to various fields in the modern information society. In this work we applied the Independent Component Analysis method to the extraction of the f...
In this paper, we propose an unsupervised approach for identifying bipolar person names in a set of topic documents. We employ principal component analysis (PCA) to discover bipol...