Theoretical foundation of a Textured Decomposition algorithm
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A Textured Decomposition Method (TDM) is proposed for large-scale convex optimization problems, in which a problem is reduced to a set of more tractable subproblems by rotatingly fixing some complicating (interaction or coupling) variables. The approach is appealing since mutually independent subproblems can be solved in parallel. Accordingly, the TDM solves a large-scale convex optimization problem by iteratively solving a sequence of concurrent subproblems. Necessary and sufficient conditions to guarantee that the converged solution of the TDM be the optimal solution of the original problem are addressed.
author list (cited authors)
HUANG, G. M., HSIEH, S. C., & COUNCIL, A.