Special Issue: Machine learning in design

Hybrid and Ensemble Methods in Machine Learning J.UCS Special Issue

Hybrid and ensemble methods in machine learning have attracted a great attention of the scientific community over the last years [Zhou, 12]. Multiple, ensemble learning models have been theoretically and empirically shown to provide significantly better performance than single weak learners, especially while dealing with high dimensional, complex regression and classification problems [Brazdil,...

Special issue on machine learning and data engineering in robotics

With the growth of sensor data and networked devices, machine learning has been gaining interest both in robotics and many other disciplines. The collaboration between machine learning and data engineering in robotics could have a strong impact on the way robots or services help our lives as well as on deepening our understanding of human intelligence. This special issue attempts to showcase st...

Special Issue

Special Issue: Organizational Design: Learning to Design Organizations and Learning from Designing Them

Special issue: Uncertainties in geometric design

In computing, it is a basic fact that, owing to the finiteness in representation, errors occur and they accumulate. In geometric computing, the 'logic' for performing set operations is not necessarily the classical binary one. How, then, does one ensure a robust process, if not error-free results? Physically, uncertainty in geometric data manifests itself in metrological studies in the small, a...