Minimax separation of the Cauchy kernel
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We prove and apply an optimal low-rank approximation of the Cauchy kernel over separated real domains. A skeleton decomposition is the minimum over real-valued functions of the maximum relative pointwise error. We establish a numerically stable form for the decomposition and demonstrate an example for which it is arbitrarily more accurate than singular value decompositions.
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