Linear convergence of an alternating polar decomposition method for low rank orthogonal tensor approximations

@article{Hu2019LinearCO,
  title={Linear convergence of an alternating polar decomposition method for low rank orthogonal tensor approximations},
  author={Shenglong Hu and Ke Ye},
  journal={Mathematical Programming},
  year={2019}
}
  • Shenglong HuKe Ye
  • Published 9 December 2019
  • Mathematics, Computer Science
  • Mathematical Programming
Low rank orthogonal tensor approximation (LROTA) is an important problem in tensor computations and their applications. A classical and widely used algorithm is the alternating polar decomposition method (APD). In this article, an improved version iAPD of the classical APD is proposed. For the first time, all the following four fundamental properties are established for iAPD: (i) the algorithm converges globally and the whole sequence converges to a KKT point without any assumption; (ii) it… 

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