Hölder Error Bounds and Hölder Calmness with Applications to Convex Semi-infinite Optimization

Alexander Y. Kruger, Marco A. López, Xiaoqi Yang, Jiangxing Zhu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)


Using techniques of variational analysis, necessary and sufficient subdifferential conditions for Hölder error bounds are investigated and some new estimates for the corresponding modulus are obtained. As an application, we consider the setting of convex semi-infinite optimization and give a characterization of the Hölder calmness of the argmin mapping in terms of the level set mapping (with respect to the objective function) and a special supremum function. We also estimate the Hölder calmness modulus of the argmin mapping in the framework of linear programming.

Original languageEnglish
Pages (from-to)995-1023
Number of pages29
JournalSet-Valued and Variational Analysis
Issue number4
Publication statusPublished - Dec 2019


  • Convex programming
  • Hölder calmness
  • Hölder error bounds
  • Semi-infinite programming

ASJC Scopus subject areas

  • Analysis
  • Statistics and Probability
  • Numerical Analysis
  • Geometry and Topology
  • Applied Mathematics

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