We present a novel affective goal selection mechanism for decision-making in agents with limited computational resources (e.g., such as robots operating under real-time constraint...
With large amounts of correlated probabilistic data being generated in a wide range of application domains including sensor networks, information extraction, event detection etc.,...
We present a parameter free approach that utilizes multiple cues for image segmentation. Beginning with an image, we execute a sequence of bottom-up aggregation steps in which pix...
In this paper, we present a robust method for estimating the model parameters in a mixture of probabilistic principal component analyzers. This method is based on the Stochastic v...
In several organizations, it has become increasingly popular to document and log the steps that makeup a typical business process. In some situations, a normative workflow model o...