Applications of the method of partial inverses to convex programming: Decomposition
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- Spingarn, J.E. Mathematical Programming (1985) 32: 199. doi:10.1007/BF01586091
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A primal–dual decomposition method is presented to solve the separable convex programming problem. Convergence to a solution and Lagrange multiplier vector occurs from an arbitrary starting point. The method is equivalent to the proximal point algorithm applied to a certain maximal monotone multifunction. In the nonseparable case, it specializes to a known method, the proximal method of multipliers. Conditions are provided which guarantee linear convergence.