Machine Learning algorithms can act as a valuable analytical tool in design research. In this paper, we demonstrate the application of a decision tree learning algorithm for desig...
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. A common way to measure performance in these domains is to use precision and recall i...
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...
Terascale simulations produce data that is vast in spatial, temporal, and variable domains, creating a formidable challenge for subsequent analysis. Feature extraction as a data r...
This paper presents the concepts of our MoRob (Modular Educational Robotic Toolbox) project, which aims to provide a robot platform for university teaching and research. Character...