Abstract. Exploiting the diversity of hypotheses produced by evolutionary learning, a new ensemble approach for Feature Selection is presented, aggregating the feature rankings ext...
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Resource selection is fundamental to the performance of master/slave applications. In this paper, we address the problem of promoting performance for distributed master/slave appl...
We consider the problem of selecting the best system using simulation-based ordinal optimization. This problem has been studied mostly in the context of light-tailed distributions...
While many works have been devoted to service matchmaking and modeling nonfunctional properties, the problem of matching service requests to offers in an optimal way has not yet b...