Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit ...
In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of training images labeled ...
"These course notes are addressed to a wide audience of people interested in modern programming languages in general, ML-like languages in particular, or simply in OCaml, whet...
In learning theory and genetic programming, OBDDs are used to represent approximations of Boolean functions. This motivates the investigation of the OBDD complexity of approximatin...
: Having evolved from volume visualisation, volume graphics is emerging as an important sub-field of computer graphics. This paper focuses on a fundamental aspect of volume graphic...