We describe a framework that helps students learn from examples by generating example problem solutions whose level of detail is tailored to the students' domain knowledge. T...
This paper proposes a data-driven method for concept-to-text generation, the task of automatically producing textual output from non-linguistic input. A key insight in our approac...
In this paper, we combine a powerful representation for graph colouring problems with different heuristic strategies for colour assignment. Our novel strategies employ heuristics ...
Cell-DEVS enables efficient execution of complex cellular models. The goal of Cell-DEVS is to build discrete-event cell spaces, improving their definition by making the timing spe...
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...