We consider a conic-quadratic (and in particular a quadratically constrained) optimization problem with uncertain data, known only to reside in some uncertainty set U. The robust ...
We study best approximation problems with nonlinear constraints in Hilbert spaces. The strong "conical hull intersection property" (CHIP) and the "basic constraint q...
This paper addresses the need for nonlinear programming algorithms that provide fast local convergence guarantees no matter if a problem is feasible or infeasible. We present an a...
We give several versions of local and global inverse mapping theorem for tame non necessarily smooth, mappings. Here tame mapping means a mapping which is subanalytic or, more gene...
Toshizumi Fukui, Krzysztof Kurdyka, Laurentiu Paun...
We consider random approximations to deterministic optimization problems. The objective function and the constraint set can be approximated simultaneously. Relying on concentratio...