Thus, the algorithm optimizes the surrogate and suggests the hyperparameter values at the maximum of the surrogate model as the optimal values for the original function as well.

We consider novel methods for the computation of model selection criteria in missing-data problems based on the output of the EM algorithm. The methodology is very general and can be applied to ...

ModelFinder is a fast model-selection method that greatly improves the accuracy of phylogenetic estimates.

The lasso, the LARS algorithm and the non-negative garrotte are recently proposed regression methods that can be used to select individual variables. We study and propose efficient algorithms for the ...

Second-order: By contrast, second-order algorithms model the surface with a quadratic surrogate model then jump to the model minimum. These include Newton-like or successive quadratic algorithms. If ...