Reconstruction and Subgaussian Operators in Asymptotic Geometric Analysis
We present a randomized method to approximate any vector from a set. The data one is given is the set T, vectors of and k scalar products, where are i.i.d. isotropic subgaussian random vectors in R, and N. We show that with high probability, any which is
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|Source:||Geometric and Functional Analysis|
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