Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
Abstract. We consider the problem of computing Nash Equilibria of action-graph games (AGGs). AGGs, introduced by Bhat and Leyton-Brown, is a succinct representation of games that e...
Constantinos Daskalakis, Grant Schoenebeck, Gregor...
There are various representations for encoding graph structures, such as artificial neural networks (ANNs) and circuits, each with its own strengths and weaknesses. Here we analyz...
The merit of automatic graph layout algorithms is typically judged by their computational efficiency and the extent to which they conform to aesthetic criteria (for example, minim...
Helen C. Purchase, Jo-Anne Allder, David A. Carrin...
In this paper, we propose a modification to the Boykov-Kolmogorov maximum flow algorithm [2] in order to make the algorithm preserve the topology of an initial interface. This alg...