Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
—The recently developed small wireless devices ranging from sensor boards to mobile phones provide a timely opportunity to gather unique data sets on complex human interactions, ...
In this paper we investigate an approach to provide approximate, anytime algorithms for DCOPs that can provide quality guarantees. At this aim, we propose the divide-and-coordinat...
Meritxell Vinyals, Marc Pujol, Juan A. Rodrí...
Given a transportation network having source nodes with evacuees and destination nodes, we want to find a contraflow network configuration (that is, ideal direction for each edge) ...
Relationships between concepts account for a large proportion of semantic knowledge. We present a nonparametric Bayesian model that discovers systems of related concepts. Given da...
Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griff...