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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Afterwards, we prove that, un-der suitable conditions, the proposed algorithm converges strongly to the metric projectionof some point onto the zero set of the involving maximal monotone operator.
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper, we consider a proximal point algorithm for finding zeros of maximal mono-tone operators in complete CAT(0) spaces.
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Key Findings & Data:First, a necessary and sufficient condition ispresented for the zero set of the operator to be nonempty.
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Conclusion & Impact:Afterwards, we prove that, un-der suitable conditions, the proposed algorithm converges strongly to the metric projectionof some point onto the zero set of the involving maximal monotone operator.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In this paper, we consider a proximal point algorithm for finding zeros of maximal mono-tone operators in complete CAT(0) spaces. First, a necessary and sufficient condition ispresented for the zero set of the operator to be nonempty. Afterwards, we prove that, un-der suitable conditions, the proposed algorithm converges strongly to the metric projectionof some point onto the zero set of the involving maximal monotone operator.
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Cite This Article
TAHERNİA, M., MORADİ, S., JAFARİ, S. (2022). The strong convergence of a proximal pointalgorithm in complete CAT(0) metric spaces. Hacettepe Journal of Mathematics and Statistics, Cilt: 49 - Sayı: 1, 399–408. https://ajindex.com/articles/529565