We consider Bayesian information collection, in which a measurement policy collects information to support a future decision. This framework includes ranking and selection, continu...
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Image parsing remains difficult due to the need to combine
local and contextual information when labeling a
scene. We approach this problem by using the epitome as a
prior over ...
Jonathan Warrell, Simon J. D. Prince, Alastair P. ...
Abstract. Concept approximation is an inference service for Description Logics that provides “translations” of concept descriptions from one DL to a less expressive DL. In [4] ...