When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
: Mobile learning has left the status of a new born child. It is time now to implement some structure into the complex and various activities by a framework presented in this paper...
Subdivision surfaces are generated by repeated approximation or interpolation from initial control meshes. In this paper, two new nonlinear subdivision schemes, face based subdivi...
This paper presents a novel context-based approach to find reliable recommendations for trust model in ubiquitous environments. Context is used in our approach to analyze the user...