Tensor Trains Approximation Estimates in the Chebyshev Norm


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A new elementwise bound on the cross approximation error used for approximating multi-index arrays (tensors) in the format of a tensor train is obtained. The new bound is the first known error bound that differs from the best bound by a factor that depends only on the rank of the approximation \(r\) and on the dimensionality of the tensor \(d\), and the dependence on the dimensionality at a fixed rank has only the order \({{d}^{{{\text{const}}}}}\) rather than constd. Thus, this bound justifies the use of the cross method even for high dimensional tensors.

Sobre autores

A. Osinsky

Institute of Numerical Mathematics, Russian Academy of Sciences

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Email: o@list.ru
Rússia, Moscow, 119333

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