Appendix of " Domain Adaptation as a Problem of Inference on Graphical Models " A1. Examples to Illustrate the Difference between Causal Graph and Our Augmented DAG

Here is an example showing the benefits of a Bayesian treatment. Two remarks are worth making on this procedure. The details will be given in the next section. The log-likelihood terms in Eq. (5) can be considered as empirical estimation of the Kullback-Leibler (KL) divergence between the data distribution and model distribution. For simplicity of notations, we assume all the source domains are of the same sample size, i.e., Finally, we can make use of Eq.