A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
Variance is a classical measure of a point estimator's sampling error. In steady-state simulation experiments, many estimators of this variance--or its square root, the stand...
A cross-validation error estimator is obtained by repeatedly leaving out some data points, deriving classifiers on the remaining points, computing errors for these classifiers on ...
We investigate the conception that the sample variance of the control variate (CV) should be used for estimating the optimal linear CV weight, even when the CV variance is known. ...
In multimodal function optimization, niching techniques create diversification within the population, thus encouraging heterogeneous convergence. The key to the effective diversif...