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arxiv: 1402.5011 · v2 · pith:M2UNT6BWnew · submitted 2014-02-20 · 🧮 math.NA

Tractability of the approximation of high-dimensional rank one tensors

classification 🧮 math.NA
keywords problemparameterstractablealgorithmsapproximationcomplexitydifficultdimension
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We study the approximation of high-dimensional rank one tensors using point evaluations and consider deterministic as well as randomized algorithms. We prove that for certain parameters (smoothness and norm of the $r$th derivative) this problem is intractable while for other parameters the problem is tractable and the complexity is only polynomial in the dimension for every fixed $\varepsilon>0$. For randomized algorithms we completely characterize the set of parameters that lead to easy or difficult problems, respectively. In the "difficult" case we modify the class to obtain a tractable problem: The problem gets tractable with a polynomial (in the dimension) complexity if the support of the function is not too small.

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