Saved in:
Bibliographic Details
Main Authors: Kanzow, Christian, Lehmann, Leo
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2605.26909
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866918524624044032
author Kanzow, Christian
Lehmann, Leo
author_facet Kanzow, Christian
Lehmann, Leo
contents We consider the optimization problem of minimizing a nonsmooth function characterized by a nonsmooth formulation of the descent lemma over a manifold. In the unconstrained case over a Euclidean space, this class of functions is called upper-$\mathcal{C}^2$. Using the recent notion of projectional subdifferentials, we show that their descent property carries over to submanifolds. We propose a nonmonotone subgradient method to solve these problems and prove stationarity of accumulation points of the generated sequence as well as convergence and rate-of-convergence results under the Kurdyka-Lojasiewicz property. We also perform numerical experiments and show how our approach can be applied to a certain type of difference of convex functions as well as clustering problems on manifolds.
format Preprint
id arxiv_https___arxiv_org_abs_2605_26909
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Nonmonotone Descent Method for Optimization Problems Defined by Upper-$\mathcal{C}^2 $ Functions over Submanifolds
Kanzow, Christian
Lehmann, Leo
Optimization and Control
We consider the optimization problem of minimizing a nonsmooth function characterized by a nonsmooth formulation of the descent lemma over a manifold. In the unconstrained case over a Euclidean space, this class of functions is called upper-$\mathcal{C}^2$. Using the recent notion of projectional subdifferentials, we show that their descent property carries over to submanifolds. We propose a nonmonotone subgradient method to solve these problems and prove stationarity of accumulation points of the generated sequence as well as convergence and rate-of-convergence results under the Kurdyka-Lojasiewicz property. We also perform numerical experiments and show how our approach can be applied to a certain type of difference of convex functions as well as clustering problems on manifolds.
title A Nonmonotone Descent Method for Optimization Problems Defined by Upper-$\mathcal{C}^2 $ Functions over Submanifolds
topic Optimization and Control
url https://arxiv.org/abs/2605.26909