We present an objective approach for evaluating probability elicitation methods in probabilistic models. Our method draws on ideas from research on learning Bayesian networks: if ...
Wepropose a cooperative conceptual modelling environment in which two agents interact : the machineand the humanexpert. Theformer is able to extract knowledge from data using a sy...
Robot projects are often evolutionary dead ends, with the software and hardware they produce disappearing without trace afterwards. Common causes include dependencies on uncommon ...
Paul M. Fitzpatrick, Giorgio Metta, Lorenzo Natale
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...