Abstract. This paper extends previously proposed bound propagation algorithm [11] for computing lower and upper bounds on posterior marginals in Bayesian networks. We improve the b...
There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewe...
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and synthesizing figure motion has employed eit...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Ke...
We propose an approximate Bayesian approach for unsupervised feature selection and density estimation, where the importance of the features for clustering is used as the measure f...
Probabilistic expert systemsbased on Bayesian networks(BNs)require initial specification both a qualitative graphical structure and quantitative assessmentof conditional probabili...