Abstract. Active Learning methods rely on static strategies for sampling unlabeled point(s). These strategies range from uncertainty sampling and density estimation to multi-factor...
One motivation for many agent-based models is to predict the future. The nonlinearity of agent interactions in most non-trivial domains mean that the usefulness of such prediction...
H. Van Dyke Parunak, Theodore C. Belding, Sven A. ...
I present a new estimation-of-distribution approach to program evolution where distributions are not estimated over the entire space of programs. Rather, a novel representationbui...
— Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of pot...
Abstract. We study in this paper several scheduling heuristics for GridRPC middlewares. When dealing with performance issue, the scheduling strategy is one of the most important fe...