Workshop on Structure Adapting Methods - Abstract
Diederichs, Elmar
Sparse NonGaussian component analysis is an unsupervised, linear, iterative and structure adaptive extraction method for semiparametric high dimensional data analysis based on estimating low-dimensional non-Gaussian components of the high-dimensional data. We propose a simplified approach to that method based on semidfinite programming that allows to improve the statistical sensitivity to a broad variety of devitations from normality while decreasing its computational effort. The new approach is demonstrated an high dimensional data sets obtained from MD-simulations of proteins.