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Paper detail

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

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.

preprint2019arXivOpen access
Alexander KrugerMarco LópezXiaoqi YangJiangxing Zhu
math.OC
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Alexander KrugerMarco LópezXiaoqi YangJiangxing Zhu

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