A sparse rank-1 approximation algorithm for high-order tensors

For the best sparse rank-1 approximation to higher-order tensors, we propose a proximal alternating minimization method in which each iteration can be easily computed. Its global convergence is established without any assumption and the numerical experiments are provided to show the efficiency of the proposed method. (C) 2019 Elsevier Ltd. All rights reserved.