Weak and strong convergence of generalized proximal point algorithms with relaxed parameters

In this work, we propose and study a framework of generalized proximal point algorithms associated with a maximally monotone operator. We indicate sufficient conditions on the regularization and relaxation parameters of generalized proximal point algorithms for the equivalence of the boundedness of...

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Veröffentlicht in:	Journal of global optimization 2023-04, Vol.85 (4), p.969-1002
1. Verfasser:	Ouyang, Hui
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Computer Science Convergence Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Parameters Real Functions Regularization Regularization methods Theorems
Online-Zugang:	Volltext
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