Abstract: Random convex programs (RCPs) are convex optimization problems subject to a finite number of constraints that are extracted at random according to some probability distribution. The optimal ...

We consider convex optimization problems with N randomly drawn convex constraints. Previous work has shown that the tails of the distribution of the probability that the optimal solution subject to ...

Abstract. In this paper, by using the notion of convexificator, we introduce the generalized standard Abadie constraint qualification and the generalized MPVC Abadie constraint qualification, and ...

A framework is proposed for solving general convex quadratic programs (CQPs) from an infeasible starting point by invoking an existing feasible-start algorithm tailored for inequality-constrained CQPs ...

Discover a novel smoothing function method for convex quadratic programming problems with mixed constraints. Explore its applications in mechanics and engineering science. Find out how this method ...

LCQPow is a open-source solver for Quadratic Programs with Complementarity Constraints. The approach is based on a standard penalty homotopy reformulated using sequential convex programming. The ...

Due to the limitations of tractable convex programs non-convex recovery approaches have been investigated intensively in the last years. In particular, the alternating and thresholding based algorithm ...

Although numerous constraints have been proposed for dual quadric reconstruction, we found that many of them are imprecise and provide minimal improvements to localization. After scrutinizing the ...

Shape constraints: Qualitative assumptions imposed on the form of an estimator, such as monotonicity, convexity, or log‐concavity, which guide nonparametric estimation.