We consider probabilistic constrained linear programs with general distributions for the uncertain parameters. These problems generally involve non-convex feasible sets. We develo...
Stand-alone threading libraries lack sophisticated memory management techniques. In this paper, we present a methodology that allows threading libraries that implement non-preempti...
To investigate the fundamental causes of bloat, six artificial random binary tree search spaces are presented. Fitness is given by program syntax (the genetic programming genotype)...
We describe two novel constructs for programming parallel machines with multi-level memory hierarchies: call-up, which allows a child task to invoke computation on its parent, and...
Michael Bauer, John Clark, Eric Schkufza, Alex Aik...
Abstract. This paper describes a new approach for parameter optimization that uses a novel representation for the parameters to be optimized. By using genetic programming, the new ...