Tensor Trains Approximation Estimates in the Chebyshev Norm
- 作者: Osinsky A.I.1
-
隶属关系:
- Institute of Numerical Mathematics, Russian Academy of Sciences
- 期: 卷 59, 编号 2 (2019)
- 页面: 201-206
- 栏目: Article
- URL: https://journal-vniispk.ru/0965-5425/article/view/180387
- DOI: https://doi.org/10.1134/S096554251902012X
- ID: 180387
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详细
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.
作者简介
A. Osinsky
Institute of Numerical Mathematics, Russian Academy of Sciences
编辑信件的主要联系方式.
Email: o@list.ru
俄罗斯联邦, Moscow, 119333
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