Beta random projection

Abstract

Random projection (RP) is a common technique for dimensionality reduction under L 2 norm for which many significant space embedding results have been demonstrated. In particular, random projection techniques can yield sharp results for R d under the L 2 norm in time linear to the product of the number of data points and dimensionalities in question. Inspired by the use of symmetric probability distributions in previous work, we propose a RP algorithm based on the hyper-spherical symmetry and give its probabilistic analyses based on Beta and Gaussian distribution. © 2008 Springer Berlin Heidelberg.