Abstract. One of the goals of augmented cognition is creation of adaptive human-machine collaboration that continually optimizes performance of the human-machine system. Augmented ...
Tjerk de Greef, Kees van Dongen, Marc Grootjen, Ja...
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...