Abstract
Fermat’s rule (Theorem 16.2) provides a simple characterization of the minimizers of a function as the zeros of its subdifferential. This chapter explores various consequences of this fact. 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). Fermat’s Rule in Convex Optimization. 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_26
Download citation
DOI: https://doi.org/10.1007/978-1-4419-9467-7_26
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)