Several important network applications cannot easily scale to higher data rates without requiring focusing just on the large traffic flows. Recent works have discussed algorithmic...
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
The ability to construct CAD or other object models from edge and range data has a fundamental meaning in building a recognition and positioning system. While the problem of model...
The problem of obtaining the maximum a posteriori (map) estimate of a discrete random field is of fundamental importance in many areas of Computer Science. In this work, we build ...
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...