A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
This paper examines the problem of estimating linear time-invariant state-space system models. In particular it addresses the parametrization and numerical robustness concerns tha...
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
Microaggregation is a statistical disclosure control technique. Raw microdata (i.e. individual records) are grouped into small aggregates prior to publication. With fixed-size grou...
Josep Domingo-Ferrer, Josep Maria Mateo-Sanz, Anna...
In this paper, we describe how user-adapted explanations about drug prescriptions can be generated from already existing data sources. We start by illustrating the two-step approa...
Fiorella de Rosis, Floriana Grasso, Dianne C. Berr...