| Special Issue on Polynomial and Tensor Optimization | 
																
																
                        | Words from the guest editors:  S. Zhang, Z. Li and S. Ma | 
                      
																
                        Paula Alexandra Amaral and Immanuel M. Bomze 
																		Copositivity-based approximations
for mixed-integer fractional quadratic optimization | 
                      
																
                        Zi Xu and Mingyi Hong 
																			Approximation bound analysis for the standard multi-quadratic optimization problem 
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                        Chen Ling, Xinzhen Zhang and Liqun Qi 
																			Approximation algorithm for a mixed binary quadratically constrained quadratic programming problem 
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                        Meilan Zeng and Qin Ni Quasi-Newton method for computing Z-eigenpairs of  a symmetric tensor | 
                      
																
                        Chun-Lin Hao,Chun-Feng Cui and Yu-Hong Dai A feasible trust-region  method for calculating  extreme Z-eigenvalues of symmetric tensors | 
                      
																
                        André Uschmajew A new convergence proof for the higher-order power method and generalizations | 
                      
																
                        Xu Kong and Deyu Meng 
                        The bounds for the best rank-1 approximation ratio of a finite dimensional
                        tensor space | 
                      
																
                        Bo Huang, Cun Mu, Donald Goldfarb and John Wright 
																				Provable models for robust low-rank tensor completion | 
                      
																
                        Min Zhang and Zheng-Hai Huang 
																				Conditions for the equivalence between the low-n-rank tensor recovery problem and its convex relaxation | 
                      
																
                        Xiang Gao, Bo Jiang and Shaozhe Tao Recovering low CP/Tucker ranked tensors, with applications in tensor completion | 
                      
																
                        Xianchao Xiu and Lingchen Kong 
																		Rank-min-one and sparse tensor decomposition for surveillance video | 
                      
																
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