Current manufacturing methods for robotic-controlled assembly rely on accurate positioning to ensure task completion, often through the use of special xtures and precise calibrati...
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
We consider automated decision aids that help users select the best solution from a large set of options. For such tools to successfully accomplish their task, eliciting and repre...
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
We present a theory of a modeler's problem decomposition skills in the context of optimal reasonzng -- the use of qualitative modeling to strategically guide numerical explor...