Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/289042 
Authors: 
Year of Publication: 
2020
Citation: 
[Journal:] Optimization Letters [ISSN:] 1862-4480 [Volume:] 15 [Issue:] 2 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2020 [Pages:] 405-418
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
In this work, we give a tight estimate of the rate of convergence for the Halpern-iteration for approximating a fixed point of a nonexpansive mapping in a Hilbert space. Specifically, using semidefinite programming and duality we prove that the norm of the residuals is upper bounded by the distance of the initial iterate to the closest fixed point divided by the number of iterations plus one.
Subjects: 
Halpern-iteration
Fixed point methods
First order methods
Semidefinite programming
Performance estimation
Proximal point
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.