Ontology alignment (or matching) is the operation that takes two ontologies and produces a set of semantic correspondences (usually semantic similarities) between some elements of ...
We present two methods for lossy compression of normal vectors through quantization using "base" polyhedra. The first revisits subdivision-based quantization. The second...
A new class of Support Vector Machine (SVM) that is applicable to sequential-pattern recognition such as speech recognition is developed by incorporating an idea of non-linear tim...
The paper presents a new vector quantization based approach for selecting well-suited data for hand-eye calibration from a given sequence of hand and eye movements. Data selection...
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
Nello Cristianini, Colin Campbell, John Shawe-Tayl...