Blocking is a technique commonly used in manual statistical analysis to account for confounding variables. However, blocking is not currently used in automated learning algorithms...
If you have ever watched movies or television shows, you know how easy it is to tell the good characters from the bad ones. Little, however, is known “whether” or “how” com...
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...
Class-instance label propagation algorithms have been successfully used to fuse information from multiple sources in order to enrich a set of unlabeled instances with class labels...
Zornitsa Kozareva, Konstantin Voevodski, Shang-Hua...
This paper studies two types of spatial relationships that can be learned from training examples for object recognition. The first one employs deformable relationships between obj...