Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
Mechatronic systems are embedded software systems with hard real-time requirements. Predictability is of paramount importance for these systems. Thus, their design has to take the...
Sven Burmester, Matthias Gehrke, Holger Giese, Sim...
Phase change memory (PCM) is an emerging memory technology for future computing systems. Compared to other non-volatile memory alternatives, PCM is more matured to production, and...
Graphs or networks can be used to model complex systems. Detecting community structures from large network data is a classic and challenging task. In this paper, we propose a nove...