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- W4387156699 abstract "We propose a numerical method to obtain an adequate value for the upper bound on the rank for the tensor completion problem on the variety of third-order tensors of bounded tensor-train rank. The method is inspired by the parametrization of the tangent cone derived by Kutschan (2018). A proof of the adequacy of the upper bound for a related low-rank tensor approximation problem is given and an estimated rank is defined to extend the result to the low-rank tensor completion problem. Some experiments on synthetic data illustrate the approach and show that the method is very robust, e.g., to noise on the data." @default.
- W4387156699 created "2023-09-30" @default.
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- W4387156699 date "2023-09-26" @default.
- W4387156699 modified "2023-10-14" @default.
- W4387156699 title "Rank Estimation for Third-Order Tensor Completion in the Tensor-Train Format" @default.
- W4387156699 doi "https://doi.org/10.48550/arxiv.2309.15170" @default.
- W4387156699 hasPublicationYear "2023" @default.
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