Abstract. We present a probabilistic model for robust principal component analysis (PCA) in which the observation noise is modelled by Student-t distributions that are independent ...
Recently, Narozny et al [1] proposed a new viewpoint in variable high-rate transform coding. They showed that the problem of finding the optimal 1-D linear block transform for a ...
In this research, a systematic study is conducted of four dimension reduction techniques for the text clustering problem, using five benchmark data sets. Of the four methods -- Ind...
Bin Tang, Michael A. Shepherd, Malcolm I. Heywood,...
Abstract. We present a set of gradient based orthogonal and nonorthogonal matrix joint diagonalization algorithms. Our approach is to use the geometry of matrix Lie groups to devel...
We propose a new ensembling method of Support Vector Machines (SVMs) based on Feature Space Restructuring. In the proposed method, the weighted majority voting method is applied f...