Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Abstract. We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated acc...
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton...
Computer-aided surgical interventions in both manual and robotic procedures have been shown to improve patient outcomes and enhance the skills of the human physician. Tool trackin...
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
Agent-based applications have the potential to assist humans in their lifestyle change, for instance eliminating addictive behaviours or adopting new healthy behaviours. In order t...
Michel C. A. Klein, Nataliya M. Mogles, Jan Treur,...