Accurately evaluating statistical independence among random variables is a key element of Independent Component Analysis (ICA). In this paper, we employ a squared-loss variant of ...
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
An efficient adaptive multigrid level set method for front propagation purposes in three dimensional medical image processing and segmentation is presented. It is able to deal with...
Marc Droske, Bernhard Meyer, Martin Rumpf, Carlo S...
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...