We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
— We study a simple game theoretic model for the spread of an innovation in a network. The diffusion of the innovation is modeled as the dynamics of a coordination game in which ...
— We introduce a hypergraph based interference model for scheduling in wireless networks. As a generalization of the graph model, hypergraph considers the conflicts caused by su...
A partitioning of a set of n items is a grouping of these items into k disjoint, equally sized classes. Any partition can be modeled as a graph. The items become the vertices of th...
We present a novel graph ranking model to extract a diverse set of answers for complex questions via random walks over a negative-edge graph. We assign a negative sign to edge weig...