In recent years, there is a growing interest in learning Bayesian networks with continuous variables. Learning the structure of such networks is a computationally expensive proced...
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit observations, as they are read from a database, we call the process stru...
Traditionally, research in identifying structured entities in documents has proceeded independently of document categorization research. In this paper, we observe that these two t...
In this paper, a Bayesian self-calibration approach using sequential importance sampling (SIS) is proposed. Given a set of feature correspondences tracked through an image sequenc...
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...