Abstract. We study the implementation on grid systems of an efficient algorithm for demanding global optimization problems. Specifically, we consider problems arising in the geneti...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
The ability to predict the quality of a software object can be viewed as a classification problem, where software metrics are the features and expert quality rankings the class lab...
The design of hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this work, we use Genetic Programming (GP) to evolve robust and fa...
The application of genetic algorithms (GAs) to many optimization problems in organizations often results in good performance and high quality solutions. For successful and efficien...
Maroun Bercachi, Philippe Collard, Manuel Clergue,...