We apply nonparametric hierarchical Bayesian modelling to relational learning. In a hierarchical Bayesian approach, model parameters can be "personalized", i.e., owned b...
Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Pe...
TheexactlikelihoodfunctionofaGaussianvectorautoregressive-movingaverage(VARMA)model is evaluated in two nonstandard cases: (a) a parsimonious structured form, such as obtained in ...
We investigate the problem of deriving precision estimates for bootstrap quantities. The one major stipulation is that no further bootstrapping will be allowed. In 1992, Efron der...
The search space of Bayesian Network structures is usually defined as Acyclic Directed Graphs (DAGs) and the search is done by local transformations of DAGs. But the space of Baye...
A Bayesian marked point process (MPP) model is developed
to detect and count people in crowded scenes. The
model couples a spatial stochastic process governing number
and placem...