We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
This paper presents methods for detection and reconstruction of `missing' data in image sequences which can be modelled using 3-dimensional autoregressive (3DAR) models. The ...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Architects use sketching and diagramming in their design process to perform functional reasoning, formal arrangements, analogy transfer, structure mapping, and knowledge acquisiti...
Word sense disambiguation for unrestricted text is one of the most difficult tasks in the fields of computational linguistics. The crux of the problem is to discover a model that ...