Summary: We present a new R package for the assessment of the reliability of clusters discovered in high dimensional DNA microarray data. The package implements methods based on r...
We wish to match sets of images to sets of images where both sets are undergoing various distortions such as viewpoint and lighting changes. To this end we have developed a Joint ...
Abstract. In contrast to the traditional hypothesis-driven methods, independent component analysis (ICA) is commonly used in functional magnetic resonance imaging (fMRI) studies to...
In this paper we present denoising algorithms for enhancing noisy signals based on Local ICA (LICA), Delayed AMUSE (dAMUSE) and Kernel PCA (KPCA). The algorithm LICA relies on app...
Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...
Chris H. Q. Ding, Ding Zhou, Xiaofeng He, Hongyuan...