We develop the necessary theory in computational algebraic geometry to place Bayesian networks into the realm of algebraic statistics. We present an algebra
Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
This paper introduces an information theoretic approach to verification of modular causal probabilistic models. We assume systems which are gradually extended by adding new functi...
Recent years have witnessed the emergence and rapid growth of distributed service infrastructures such as mobile ad hoc networks, P2P, PlanetLab and Grids. In such distributed inf...
There are many key problems of decision making related to spectrum occupancies in cognitive radio networks. It is known that there exist correlations of spectrum occupancies in tim...