The robust isolated calmness of spectral norm regularized convex matrix optimization problems
This article aims to provide a series of characterizations of the robust isolated calmness of the Karush-Kuhn-Tucker (KKT) mapping for spectral norm regularized convex optimization problems. By establishing the variational properties of the spectral norm function, we directly prove that the KKT mapp...
Saved in:
| Main Authors: | Yin Ziran, Chen Xiaoyu, Zhang Jihong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2025-08-01
|
| Series: | Open Mathematics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/math-2025-0189 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A comprehensive characterization of the robust isolated calmness of Ky Fan $ k $-norm regularized convex matrix optimization problems
by: Ziran Yin, et al.
Published: (2025-03-01) -
The exactness of the ℓ1 penalty function for a class of mathematical programs with generalized complementarity constraints
by: Yukuan Hu, et al.
Published: (2024-11-01) -
Modification of Adomian decomposition technique in multiplicative calculus and application for nonlinear equations
by: Farooq Ahmed Shah, et al.
Published: (2024-12-01) -
Beyond Time Calmness: The Beauties of Aging
by: Ezgican Meral
Published: (2024-04-01) -
Consensus-based optimisation with truncated noise
by: Massimo Fornasier, et al.
Published: (2025-04-01)