Recent approaches to learning structured predictors often require approximate inference for tractability; yet its effects on the learned model are unclear. Meanwhile, most learnin...
Abstract. We study the problem of mining frequent itemsets from uncertain data under a probabilistic framework. We consider transactions whose items are associated with existential...
We propose a novel, computationally efficient generative topographic model for inferring low dimensional representations of high dimensional data sets, designed to exploit data s...
: This paper presents a causal simulation method for incompletely known dynamic systems in process engineering. The causal model of a process is represented as both a causal networ...
Line localization from a single image of a central camera is an ill-posed problem unless other constraints or apriori knowledge are exploited. Recently, it has been proved that no...