Error bounds and metric subregularity
By Alexander Y. Kruger. 2014
123 citations recorded by the source corpus.
Necessary and sufficient criteria for metric subregularity (or calmness) of set-valued mappings between general metric or Banach spaces are treated in the framework of the theory of error bounds for a special family of extended real-valued functions of two variables. A classification scheme for the general error bound and metric subregularity criteria is presented. The criteria are formulated in terms of several kinds of primal and subdifferential slopes.
Subfields: Applied Mathematics, Computational Theory and Mathematics, Geometry and Topology
View Paper: https://www.semanticscholar.org/paper/f2d3308815674db6b40d79a3fb9382d878f4dcce
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In Applied Mathematics
In Computational Theory and Mathematics
- Alexander Y. Kruger
- Radek Cibulka
- Anthony Man-Cho So
- Zirui Zhou
- Asen L. Dontchev
- A. S. Lewis
- Dmitriy Drusvyatskiy
- Alexander D. Ioffe
In Geometry and Topology
Citations in the corpus
- A unified approach to error bounds for structured convex optimization problems (2015, background): “…from Before we proceed further, let us briefly illustrate some of the concepts above. and there exist constants κ, ǫ > 0 such that The notions of calmness and metric sub-regularity have played a central role in the study of error bounds; see, e.g. , [26, 9, 31, 27, 15] and the references therein.”
- Strong metric subregularity of mappings in variational analysis and optimization (2017, background): “extensively used in [26] when characterizing metric subregularity.”
- Error Bounds and Hölder Metric Subregularity (2014, methodology): “This allows one to apply to it the extension of the theory of error bounds to functions of two variables developed in [31] and used there for characterizing standard metric subregularity (case q = 1).”