This workshop is about how to design learning problems. The dominant system for applying machine learning in practice involves a human labeling data. This approach is limited to situations where human experts exist, can be afforded, and are fast enough to solve the relevant problem.
In order to better understand complex Belief-Propagation models tested with our simulator we have identified a strong need for a simple visualization tool that will grant us insight of the tested graphs.