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- W4200611640 abstract "In this paper, we consider nonseparable convex minimization models with quadratic coupling terms arised in many practical applications. We use a majorized indefinite proximal alternating direction method of multipliers (iPADMM) to solve this model. The indefiniteness of proximal matrices allows the function we actually solved to be no longer the majorization of the original function in each subproblem. While the convergence still can be guaranteed and larger stepsize is permitted which can speed up convergence. For this model, we analyze the global convergence of majorized iPADMM with two different techniques and the sublinear convergence rate in the nonergodic sense. Numerical experiments illustrate the advantages of the indefinite proximal matrices over the positive definite or the semi-definite proximal matrices." @default.
- W4200611640 created "2021-12-31" @default.
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- W4200611640 date "2021-12-13" @default.
- W4200611640 modified "2023-09-27" @default.
- W4200611640 title "Majorized iPADMM for Nonseparable Convex Minimization Models with Quadratic Coupling Terms" @default.
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- W4200611640 doi "https://doi.org/10.1142/s0217595922400024" @default.
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