Many imaging systems seek a good interpretation of the scene presented -- i.e., a plausible (perhaps optimal) mapping from aspects of the scene to real-world objects. This paper a...
Bayesian networks are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. We will analyze Bayesian network...
We propose a novel clustering method that is an extension of ideas inherent to scale-space clustering and support-vector clustering. Like the latter, it associates every data poin...
The task of generating minimal models of a knowledge base is a significant computational problem in artificial intelligence. This task is at the computational heart of diagnosis s...
We present a novel, type-logical analysis of polarity sensitivity: how negative polarity items (like any and ever) or positive ones (like some) are licensed or prohibited. It take...