Merging Multigrid Optimization with SESOP

Autor:	Hong, Tao, Yavneh, Irad, Zibulevsky, Michael
Rok vydání:	2018
Předmět:	Mathematics - Optimization and Control Mathematics - Numerical Analysis
Druh dokumentu:	Working Paper
Popis:	A merger of two optimization frameworks is introduced: SEquential Subspace OPtimization (SESOP) with MultiGrid (MG) optimization. At each iteration of the algorithm, the search direction implied by the coarse-grid correction process of MG is added to the low dimensional search-space of SESOP, which includes the preconditioned gradient and search directions involving the previous iterates, called {\em history}. Numerical experiments demonstrate the effectiveness of this approach. We then study the asymptotic convergence factor of the two-level version of SESOP-MG (dubbed SESOP-TG) for optimization of quadratic functions, and derive approximately optimal fixed parameters, which may reduce the computational overhead for such problems significantly. Comment: 8 figures, 1 table
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1812.06896 Zobrazit plný text záznamu View this record from Arxiv