Multiscale Geometric Methods for Data Sets I: Multiscale SVD, Noise and Curvature
Large data sets are often modeled as being noisy samples from probability distributions in R^D, with D large. It has been noticed that oftentimes the support M of these probability distributions seems to be well-approximated by low-dimensional sets, perhaps even by manifolds. We shall consider sets...
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2012
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| Online Access: | http://hdl.handle.net/1721.1/72597 |