This w orkshows how to train the activation function in neuro-wavelet parametric modeling and how this improves performance in a number of modeling, classi cation and forecasting.
Valentina Colla, Mirko Sgarbi, Leonardo Maria Reyn...
In this paper, we investigate the problem of deriving precision estimates for bootstrap quantities within parametric families. Efron's [1992] jackknife-after-bootstrap is a s...
Finite mixtures of parametric distributions are often used to model data of which it is known or suspected that there are subpopulations. Instead of a parametric model, a penalize...
We present a formalization of a version of Abadi and Plotkin's logic for parametricity for a polymorphic dual intuitionistic / linear type theory with fixed points, and show,...
We present a model for computing the probability of a parametric failure due to a spot defect. The analysis is based on electromigration in conductors under unidirectional current...