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Abstract
\def\iint{{\hbox{int}\;}} This paper considers the parameterized infinite dimensional optimization problem minimize{t≥0:S∩{x+tF}=∅}, where S is a nonempty closed subset of a Hilbert space H and F⊆H is closed convex satisfying 0∈∬F. The optimal value T(x) depends on the parameter x∈H, and the (possibly empty) set S∩(x+T(x)F) of optimal solutions is the ``F-projection'' of x into S. We first compute proximal and Fr\'echet subgradients of T(⋅) in terms of normal vectors to level sets, and secondly, in terms of the F-projection. Sufficient conditions are also obtained for the differentiability and semiconvexity of T(⋅), results which extend the known case when F is the unit ball
Author information
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GC
Giovanni Colombo
Dip. di Matematica Pura e Applicata, Universita di Padova, Via Belzoni 7, 35131 Padova, Italy
G. Colombo, P. R. Wolenski. “Variational Analysis for a Class of Minimal Time Functions in Hilbert Spaces.” Journal of Convex Analysis 11 (2004), No. 2, 335–361.