Background: Principal component analysis (PCA) has gained popularity as a method for the analysis of highdimensional genomic data. However, it is often difficult to interpret the ...
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
In this paper general solutions for Nonlinear Nonnegative Component Analysis for data representation and recognition are proposed. That is, motivated by a combination of the Nonne...
— To approximate complex data, we propose new type of low-dimensional “principal object”: principal cubic complex. This complex is a generalization of linear and nonlinear pr...
Alexander N. Gorban, Neil R. Sumner, Andrei Yu. Zi...
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...