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Looking for appropriate qualification conditions for subdifferential formulae and dual representations for convex risk measures

机译:寻找适合微分公式的资格条件和凸风险测度的对偶表示

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摘要

A fruitful idea, when providing subdifferential formulae and dual representations for convex risk measures, is to make use of the conjugate duality theory in convex optimization. In this paper we underline the outstanding role played by the qualification conditions in the context of different problem formulations in this area. We show that not only the meanwhile classical generalized interiority point conditions come here to bear, but also a recently introduced one formulated by means of the quasi-relative interior.
机译:在为凸风险度量提供微分公式和对偶表示时,一个富有成果的想法是在凸优化中使用共轭对偶理论。在本文中,我们强调了资格条件在该领域不同问题的表述中所起的突出作用。我们表明,不仅经典的广义内在性点条件在这里可以得到满足,而且最近引入的一种通过准相对内在性提出的条件也应运而生。

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