scholarly journals New ALS Methods With Extrapolating Search Directions and Optimal Step Size for Complex-Valued Tensor Decompositions

2011 ◽  
Vol 59 (12) ◽  
pp. 5888-5898 ◽  
Author(s):  
Yannan Chen ◽  
Deren Han ◽  
Liqun Qi
2018 ◽  
Vol 12 (1) ◽  
pp. 224-243 ◽  
Author(s):  
Abdellah Bnouhachem ◽  
Themistocles Rassias

In this paper, we suggest and analyze a new alternating direction scheme for the separable constrained convex programming problem. The theme of this paper is twofold. First, we consider the square-quadratic proximal (SQP) method. Next, by combining the alternating direction method with SQP method, we propose a descent SQP alternating direction method by using the same descent direction as in [6] with a new step size ?k. Under appropriate conditions, the global convergence of the proposed method is proved. We show the O(1/t) convergence rate for the SQP alternating direction method. Some preliminary computational results are given to illustrate the efficiency of the proposed method.


2013 ◽  
Vol 25 (23) ◽  
pp. 2327-2330 ◽  
Author(s):  
Jing Shao ◽  
Shiva Kumar ◽  
Xiaojun Liang

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