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Faster Robust Tensor Power Method for Arbitrary Order

Machine Learning 2023-06-02 v1 Numerical Analysis Numerical Analysis

Abstract

Tensor decomposition is a fundamental method used in various areas to deal with high-dimensional data. \emph{Tensor power method} (TPM) is one of the widely-used techniques in the decomposition of tensors. This paper presents a novel tensor power method for decomposing arbitrary order tensors, which overcomes limitations of existing approaches that are often restricted to lower-order (less than 33) tensors or require strong assumptions about the underlying data structure. We apply sketching method, and we are able to achieve the running time of O~(np1)\widetilde{O}(n^{p-1}), on the power pp and dimension nn tensor. We provide a detailed analysis for any pp-th order tensor, which is never given in previous works.

Keywords

Cite

@article{arxiv.2306.00406,
  title  = {Faster Robust Tensor Power Method for Arbitrary Order},
  author = {Yichuan Deng and Zhao Song and Junze Yin},
  journal= {arXiv preprint arXiv:2306.00406},
  year   = {2023}
}