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Whenever distributions tend to be locally low-dimensional, the recommended test can be manufactured better to distinguish certain options by integrating neighborhood covariance matrices and building an anisotropic kernel. The kernel matrix is asymmetric; it computes the affinity between [Formula see text] data things and a set of [Formula see text] reference points, where [Formula see text] may be considerably smaller than [Formula see text]. Although the recommended figure may very well be a

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