Among the various tasks involved in building a Bayesian network for a real-life application, the task of eliciting all probabilities required is generally considered the most daunt...
Eveline M. Helsper, Linda C. van der Gaag, Floris ...
Knowledge representation has always been a major problem in the design of medical decision support systems. In this paper we present a new methodology to represent and reason about...
We study a stochastic optimization problem that has its roots in financial portfolio design. The problem has a specified deterministic objective function and constraints on the co...
In some application domains, such as medical imaging, the objects that compose the scene are known as well as some of their properties and their spatial arrangement. We can take ad...
Olivier Nempont, Jamal Atif, Elsa D. Angelini, Isa...
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can ...