Sparse wireless sensor networks (WSNs) are being effectively used in several applications, which include transportation, urban safety, environment monitoring, and many others. Sens...
Mario Di Francesco, Kunal Shah, Mohan Kumar, Giuse...
We discuss Bayesian methods for learning Bayesian networks when data sets are incomplete. In particular, we examine asymptotic approximations for the marginal likelihood of incomp...
This tutorial paper overviews recent developments in optimization-based approaches for resource allocation problems in wireless systems. We begin by overviewing important results i...
A common statistical model for paired comparisons is the Bradley-Terry model. This research re-parameterizes the Bradley-Terry model as a single-layer artificial neural network (A...
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...