We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Most recent research in trainable part of speech taggers has explored stochastic tagging. While these taggers obtain high accuracy, linguistic information is captured indirectly, ...
When an image is viewed at varying resolutions, it is known to create discrete perceptual jumps or transitions amid the continuous intensity changes. In this paper, we study a per...
We describe a generative model for graph edges under specific degree distributions which admits an exact and efficient inference method for recovering the most likely structure. T...
We describe three applications in computational learning theory of techniques and ideas recently introduced in the study of parameterized computational complexity. (1) Using param...
Rodney G. Downey, Patricia A. Evans, Michael R. Fe...