An algorithm for learning structural patterns given in terms of Attributed Relational Graphs (ARG's) is presented. The algorithm, based on inductive learning methodologies, pr...
In some environments, a learning agent must learn to balance competing objectives. For example, a Q-learner agent may need to learn which choices expose the agent to risk and whic...
Complex triangle meshes arise naturally in many areas of computer graphics and visualization. Previous work has shown that a quadric error metric allows fast and accurate geometri...
In this paper, we introduce a new method, GraphScape, to visualize multivariate networks, i.e., graphs with multivariate data associated with their nodes. GraphScape adopts a land...
Kai Xu 0003, Andrew Cunningham, Seok-Hee Hong, Bru...
In this paper we give an overview of formal concepts for model transformations between visual languages based on typed attributed graph transformation. We start with a basic conce...