We classify an image by generating a list of salient visual features present in the luminance channel, and matching the resulting variable-length feature list to categoryspecific ...
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
Abstract. Although we can build a belief network starting from any ordering of its variables, its structure depends heavily on the ordering being selected: the topology of the netw...
We introduce a new type of graphical model called a `cumulative distribution network' (CDN), which expresses a joint cumulative distribution as a product of local functions. ...
A naive Bayesian classifier is a probabilistic classifier based on Bayesian decision theory with naive independence assumptions, which is often used for ranking or constructing a...