Abstract
As seen in Chapter 26, the solutions to variational problems can be characterized by fixed point equations involving proximity operators. Since proximity operators are firmly nonexpansive, they can be used to devise efficient algorithms to solve minimization problems. Such algorithms, called proximal algorithms, are investigated in this chapter. Throughout, K is a real Hilbert space.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Bauschke, H.H., Combettes, P.L. (2011). Proximal Minimization. In: Convex Analysis and Monotone Operator Theory in Hilbert Spaces. CMS Books in Mathematics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9467-7_27
Download citation
DOI: https://doi.org/10.1007/978-1-4419-9467-7_27
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-9466-0
Online ISBN: 978-1-4419-9467-7
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)