We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Abstract. Many graph problems seem to require knowledge that extends beyond the immediate neighbors of a node. The usual self-stabilizing model only allows for nodes to make decisi...
Wayne Goddard, Stephen T. Hedetniemi, David Pokras...
The paper compares two popular strategies for solving propositional satis ability, backtracking search and resolution, and analyzes the complexity of a directional resolution algo...
We extend our previous work on the exploration of static metabolic networks to evolving, and therefore dynamic, pathways. We apply our visualization software to data from a simulat...
Markus Rohrschneider, Alexander Ullrich, Andreas K...
The anticipation game framework is an extension of attack graphs based on game theory. It is used to anticipate and analyze intruder and administrator concurrent interactions with ...