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.
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Lu, YE., Liò, P., Hand, S. (2008). Beta Random Projection. In: Liò, P., Yoneki, E., Crowcroft, J., Verma, D.C. (eds) Bio-Inspired Computing and Communication. BIOWIRE 2007. Lecture Notes in Computer Science, vol 5151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92191-2_28
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DOI: https://doi.org/10.1007/978-3-540-92191-2_28
Publisher Name: Springer, Berlin, Heidelberg
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