Generalized Proximal Point
نویسنده
چکیده
Ha 7] recently introduced the generalized proximal point algorithm for solving the generalized equation. In this note, we present the generalized proximal point algorithm for convex optimization problems based on Ha's work. The idea behind this algorithm is that instead of adding a quadratic term to all the variables, we add a quadratic term to a subset of the variables. We extend the criteria for approximate solutions given by Rockafellar 19] and Auslender 1] and present convergence results. Finally, we show how this algorithm can be applied to solve block-angular linear and quadratic programming problems.
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