Lipschitz Stability of Least-Squares Problems Regularized by Functions with C2-Cone Reducible Conjugates

In this paper, we study Lipschitz continuity of the solution mappings of regularized least-squares problems for which the convex regularizers have (Fenchel) conjugates that are [Formula: see text]-cone reducible. Our approach, by using Robinson’s strong regularity on the dual problem, allows us to obtain new characterizations of Lipschitz stability that rely solely on first-order information, thus bypassing the need to explore second-order information (curvature) of the regularizer. We show that these solution mappings are automatically Lipschitz continuous around the points in question whenever they are locally single-valued. We leverage our findings to obtain new characterizations of full stability and tilt stability for a broader class of convex additive-composite problems. Funding: Y. Cui is partially supported by the National Science Foundation [Grant DMS-2416250] and the National Institutes of Health [Grant 1R01CA287413-01]. T. Hoheisel is supported by an NSERC Discovery grant [Grant RGPIN-2024-04116]. The research of D. Sun was supported in part by the Hong Kong Research Grants Council [Grant GRF project 15309625] and the RGC Senior Research Fellow scheme [Grant SRFS2223-5S02].

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Publication Details

Journal
Mathematics of Operations Research
Published
2026-01-05
DOI
https://doi.org/10.1287/moor.2024.0692
Primary Topic
Numerical methods in inverse problems
Type
article
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article

Lipschitz Stability of Least-Squares Problems Regularized by Functions with C2-Cone Reducible Conjugates

Tim Hoheisel, Ying Cui, Defeng Sun, Tran T. A. Nghia
Mathematics of Operations Research
Numerical methods in inverse problems
article

Lipschitz Stability of Least-Squares Problems Regularized by Functions with C2-Cone Reducible Conjugates

Tim Hoheisel, Ying Cui, Defeng Sun, Tran T. A. Nghia
article en

Abstract

In this paper, we study Lipschitz continuity of the solution mappings of regularized least-squares problems for which the convex regularizers have (Fenchel) conjugates that are [Formula: see text]-cone reducible. Our approach, by using Robinson’s strong regularity on the dual problem, allows us to obtain new characterizations of Lipschitz stability that rely solely on first-order information, thus bypassing the need to explore second-order information (curvature) of the regularizer. We show that these solution mappings are automatically Lipschitz continuous around the points in question whenever they are locally single-valued. We leverage our findings to obtain new characterizations of full stability and tilt stability for a broader class of convex additive-composite problems. Funding: Y. Cui is partially supported by the National Science Foundation [Grant DMS-2416250] and the National Institutes of Health [Grant 1R01CA287413-01]. T. Hoheisel is supported by an NSERC Discovery grant [Grant RGPIN-2024-04116]. The research of D. Sun was supported in part by the Hong Kong Research Grants Council [Grant GRF project 15309625] and the RGC Senior Research Fellow scheme [Grant SRFS2223-5S02].

Mathematics of Operations Research
Hong Kong Polytechnic University (HK), Oakland University (US), McGill University (CA), University of California, Berkeley (US)
Partnerships for the goals
Openalex Percentile: Top 94%
Numerical methods in inverse problems
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Lipschitz Stability of Least-Squares Problems Regularized by Functions with C2-Cone Reducible Conjugates — Tim Hoheisel, Ying Cui, et al. · Mathematics of Operations Research (2026) | TGRS Research Map | TGRS