arXiv Analytics

Sign in

arXiv:2311.15152 [math.OC]AbstractReferencesReviewsResources

How does the contraction property fail for convex functions on normed spaces?

Shin-ichi Ohta

Published 2023-11-26Version 1

On Euclidean and Hilbert spaces, Riemannian manifolds, and CAT$(0)$-spaces, gradient flows of convex functions are known to satisfy the contraction property, which plays a fundamental role in optimization theory and possesses fruitful analytic and geometric applications. On (non-inner product) normed spaces, however, gradient flows of convex functions do not satisfy the contraction property. We give a detailed proof of this characterization of inner products, and discuss a possible form of a weaker contraction property on normed spaces.

Related articles: Most relevant | Search more
arXiv:2307.16560 [math.OC] (Published 2023-07-31)
Line Search for Convex Minimization
arXiv:1710.10187 [math.OC] (Published 2017-10-27)
A general representation of delta-normal sets to sublevels of convex functions
arXiv:1111.0194 [math.OC] (Published 2011-11-01, updated 2012-05-24)
Optimization of Convex Functions with Random Pursuit