Abstract - Organizational learning requires individual learning. Individual learning has to interact in a dynamic social environment in order to contribute to organizational learni...
We propose an extension of the conformal (or geodesic) active contour framework in which the conformal factor depends not only on the position of the curve but also on the directi...
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...