Abstract. We consider column sufficient linear complementarity problems and study the problem of identifying those variables that are zero at a solution. To this end we propose a n...
Francisco Facchinei, Andreas Fischer, Christian Ka...
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
Anton J. Kleywegt, Alexander Shapiro, Tito Homem-d...
In this paper, we will first introduce a novel multiscale representation (MSR) for shapes via level set motions and partial differential equations (PDEs). Based on the MSR, we wi...
The aim of the paper is to provide a theoretical basis for approximate reduced SQP methods. In contrast to inexact reduced SQP methods, the forward and the adjoint problem accuraci...
Kazufumi Ito, Karl Kunisch, Volker Schulz, Ilia Gh...
We provide a logical model of biochemical reactions and show how hypothesis generation using weakest sufficient and strongest necessary conditions may be used to provide addition...
Patrick Doherty, Steve Kertes, Martin Magnusson, A...