Predicting the running time of a parallel program is useful for determining the optimal values for the parameters of the implementation and the optimal mapping of data on processo...
Many important combinatorial optimization problems can be expressed as constraint satisfaction problems with soft constraints. When problems are too difficult to be solved exactly,...
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization pro...
Our human body is well protected by antibodies from our biological immune system. This protection system matured over millions of years and has proven its functionality. In our re...
Andreas Pietzowski, Wolfgang Trumler, Theo Ungerer
We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, inst...