Decision-guided perspectives on model uncertainty expand traditional statistical thinking
about managing, comparing, and combining inferences from sets of models. In this …

Robust classification models based on the ensemble methodology are proposed in the
paper. The main feature of the models is that the precise vector of weights assigned for …

A new algorithm for ensemble construction based on adapted restricting a set of weights of
examples in training data to avoid overfitting and to reduce a number of iterations is …

This paper reviews the growing field of Bayesian prediction. Bayes point and interval
prediction are defined and exemplified and situated in statistical prediction more generally …

The boosting technique emerged from machine learning has become a widely used method
to estimate statistical models. As one of the most successful variants, componentwise …

Cortical alignment is an essential link in the processing chain for establishing neurological
relationships across multiple subjects. This thesis addresses multi-subject cortical alignment …

A new approach for ensemble construction based on restricting a set of weights of examples
in training data to avoid overfitting is proposed in the paper. The algorithm called EPIBoost …