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Finally, the multiplier associated to the last two block variables is updated.
For example, the authors of [16, 17] added an additional Gaussian back substitution correction step in each iteration after all the block variables are updated.
First of all, two subproblems are solved in a parallel fashion, and the multiplier associated to these two block variables is updated in a rapid sequence.
The recent research indicates that, due to the separable convex optimization with three block variables, the direct extension of the alternating direction method of multipliers is not necessarily convergent [10].
The problem can be reformulated as a convex minimization problem with three separable block variables, and we get the variational inequalities formulation by the KKT conditions of the separable convex minimization problem.
The former two subproblems are first solved in a parallel fashion, and immediately, the multipliers associated to these are updated; then the third subproblem is solved in the sense of an alternative fashion with the former two subproblems, and the multipliers associated to the last two block variables are updated.
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The full model includes class variable and the block variable, and the reduced model includes only the block variable.
The donor information (three donors) was considered as the block variable in the model.
With respect to the association of the questions studied with child depression, no socio-demographic block variable investigated proved to be associated (Table 2).
There are no watertight definitions of fixed and random effects [9], [20] but the basic idea can be illustrated by contrasting experimental treatments with blocking variables [21].
The area type and period variables were added as blocking variables to the initial model.
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