In this paper we report a new approach to generating predictions about skilled interactive cognition. The approach, which we call Cognitive Constraint Modeling, takes as input a d...
Alonso H. Vera, Andrew Howes, Michael McCurdy, Ric...
Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...
This paper combines predictive labeling with dependency pairs and reports on its implementation. Our starting point is the method of proving termination of rewrite systems using se...
Achieving crisp interactive response in resource-intensive applications such as augmented reality, language translation, and speech recognition is a major challenge on resource-po...
We investigate the usage of edge-based inpainting as an intra prediction method in block-based image compression. The joint utilization of edge information and the well-known Lapl...