Tensor Trains Approximation Estimates in the Chebyshev Norm
- Autores: Osinsky A.I.1
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Afiliações:
- Institute of Numerical Mathematics, Russian Academy of Sciences
- Edição: Volume 59, Nº 2 (2019)
- Páginas: 201-206
- Seção: Article
- URL: https://journals.rcsi.science/0965-5425/article/view/180387
- DOI: https://doi.org/10.1134/S096554251902012X
- ID: 180387
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Resumo
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.
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Sobre autores
A. Osinsky
Institute of Numerical Mathematics, Russian Academy of Sciences
Autor responsável pela correspondência
Email: o@list.ru
Rússia, Moscow, 119333
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