Multivariate Gaussianization for Data Processing

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Intro Iterative Gaussianization Experiments ConclusionsGaussianization“Transform multidimensional data into multivariate Gaussian data”Why?Achieve statistical independence of data components is useful to ...... process dimensions independently... alleviate the curse of dimensionality... tackle the PDF estimation problem directly... apply/design methods that assume Gaussianity safely... get insight in the data characteristics
Intro Iterative Gaussianization Experiments ConclusionsGaussianization, more formallyGiven a random variable x ∈ R d , a Gaussianization transform is an invertibleand differentiable transform G(x) such thatG(x) ∼ N (0, I)What do we need?1 Can we ‘Gaussianize’ each dimension independently?2 If not, can we look for a (hopefully linear) transform to do it?
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Multivariate Gaussianization for Data Processing

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