We present an approach to semi-supervised learning based on an exponential family characterization. Our approach generalizes previous work on coupled priors for hybrid generative/...
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood function is proposed to capture the preference relat...
Mathematical morphology was originally conceived as a set theoretic approach for the processing of binary images. Approaches that extend classical binary morphology to gray-scale ...
Turning the current Web into a Semantic Web requires automatic approaches for annotation of existing data since manual approaches will not scale in general. We here present an app...
A novel approach to calculate the generalization error of the support vector machines and a new support vector machine–nonsymmatic support vector machine–is proposed here. Our ...