Higher-degree tensor eigenvalue complementarity problems

Ruixue Zhao () and Jinyan Fan ()
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Ruixue Zhao: Shanghai Jiao Tong University
Jinyan Fan: Shanghai Jiao Tong University

Computational Optimization and Applications, 2020, vol. 75, issue 3, No 10, 799-816

Abstract: Abstract In this paper, we study the higher-degree tensor eigenvalue complementarity problem (HDTEiCP). We give an upper bound for the number of the higher-degree complementarity eigenvalues for the generic HDTEiCP. A semidefinite relaxation algorithm is proposed for computing all the higher-degree complementarity eigenvalues sequentially, as well as the corresponding eigenvectors, and the convergence of the algorithm is discussed. Some numerical results are also given.

Keywords: Higher-degree; Tensor eigenvalue; Complementarity problem; Lasserre relaxation; Semidefinite program; 65K10; 15A18; 65F15; 90C22 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10589-019-00159-w

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