At a fundamental level, the key challenge in data integration is to reconcile the semantics of disparate data sets, each expressed with a different database structure. I argue th...
- Canonical correlation analysis (CCA) is a major linear subspace approach to dimensionality reduction and has been applied to image processing, pose estimation and other fields. H...
The general aim of this talk is to advocate a combinatorial perspective, together with its methods, in the investigation and study of models of computation structures. This, of cou...
: Measuring ellipticity is an important area of computer vision systems. Most existing ellipticity measures are area based and cannot be easily applied to point sets such as extrac...
Nearest neighbour classifiers and related kernel methods often perform poorly in high dimensional problems because it is infeasible to include enough training samples to cover the...