A semidefinite algorithm for completely positive tensor decomposition

Jinyan Fan () and Anwa Zhou ()
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Jinyan Fan: Shanghai Jiao Tong University
Anwa Zhou: Shanghai University

Computational Optimization and Applications, 2017, vol. 66, issue 2, No 3, 267-283

Abstract: Abstract A symmetric tensor, which has a symmetric nonnegative decomposition, is called a completely positive tensor. In this paper, we characterize the completely positive tensor as a truncated moment sequence, and transform the problem of checking whether a tensor is completely positive to checking whether its corresponding truncated moment sequence admits a representing measure, then present a semidefinite algorithm to solve it. If a tensor is not completely positive, a certificate for it can be obtained; if it is completely positive, a nonnegative decomposition can be obtained.

Keywords: Completely positive tensor; Nonnegative decomposition; Truncated moment problem; Semidefinite program; 15A69; 44A60; 90C22 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10589-016-9870-9

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