Sparse NonGaussian Component Analysis

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• Vladimir Spokoiny (Weierstrass Institute)
• Friday 07 May 2010, 16:00-17:00
• MR12, CMS, Wilberforce Road, Cambridge, CB3 0WB.

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Non Gaussian Component Analysis is an unsupervised method of extracting a linear structure from a high dimensional data based on estimating a low-dimensional non-Gaussian data component. This paper offers a new approach to direct estimation of the projector on the target space based on semidefinite programming. The new procedure differs significantly from the earlier proposals in Blanchard et al (2006) and Diederichs et al (2010) and it improves the method efficiency and sensitivity to a broad variety of deviations from normality and decreases the computational effort. It particularly enables to proceed with much higher dimensions without loss of accuracy.

http://www.wias-berlin.de/~spokoiny/

This talk is part of the Statistics series.

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