Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Abstract. We describe methods for high-performance and high-quality rendering of point models, including advanced shading, anti-aliasing, and transparency. we keep the rendering qu...
The paper presents LOCO-Analyst, an educational tool for providing teachers with feedback on the relevant aspects of the learning process taking place in a web-based learning envir...
Jelena Jovanovic, Dragan Gasevic, Christopher A. B...
— Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction da...
A major obstacle to fully integrated deployment of many data mining algorithms is the assumption that data sits in a single table, even though most real-world databases have compl...
Alexandrin Popescul, Lyle H. Ungar, Steve Lawrence...