An improved method for generalized constrained canonical correlation analysis (GCCANO) is proposed. In the original GCCANO, data matrices were first decomposed into the sum of sev...
We introduce a new framework, namely Tensor Canonical Correlation Analysis (TCCA) which is an extension of classical Canonical Correlation Analysis (CCA) to multidimensional data ...
Background: Quantitative analysis of differential protein expressions requires to align temporal elution measurements from liquid chromatography coupled to mass spectrometry (LC/M...
In the recent years, 3D Face recognition has emerged as a major solution to deal with the unsolved issues for reliable 2D face recognition, i.e. lighting condition and viewpoint v...
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...