paper: Boosted Bayesian Network Classifiers

Jing Yushi has a ICML 2005/ ML2008 paper:
Boosted Bayesian Network Classifiers
It seems very interesting to me. Now I am using topic models to implement my ideas. But generative models usually can not beat discriminative classifiers such as SVM in many cases. It is of interests of the generative guys to combine these two methods to benefit from both. Jing's paper show the boosted version of Naive Bayesian. Can we develop boosted topic models? It is good direction. I Googled and find no such work so far.