One of the main questions that arise when studying random and quasi-random structures is which properties P are such that any object that satisfies P "behaves" like a tr...
In distributed data mining models, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose...
The problem of combining the ranked preferences of many experts is an old and surprisingly deep problem that has gained renewed importance in many machine learning, data mining, a...
Visualizing 3D flow fields intrinsically suffers from problems of clutter and occlusion. A common practice to alleviate these issues is to restrict the visualization to feature su...
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...