We develop regression diagnostics for functional regression models which relate a functional response to predictor variables that can be multivariate vectors or random functions. ...
In this paper we extend the class of energy functions for which the optimal -expansion and -swap moves can be computed in polynomial time. Specifically, we introduce a class of hi...
In this paper, we present a fast and scalable Bayesian model for improving weakly annotated data – which is typically generated by a (semi) automated information extraction (IE) ...
: Current grid technologies offer unlimited computational power and storage capacity for scientific research and business activities in heterogeneous areas all over the world. Than...
Francesco Lelli, Eric Frizziero, Michele Gulmini, ...
: This report introduces a geometrical constraint kernel for handling the location in space and time of polymorphic k-dimensional objects subject to various geometrical and time co...
Nicolas Beldiceanu, Mats Carlsson, Emmanuel Poder,...