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» Modelling Variability for System Families
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ICRA
2007
IEEE
189views Robotics» more  ICRA 2007»
14 years 2 months ago
Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
Georgios Petkos, Sethu Vijayakumar
ISIPTA
1999
IEEE
108views Mathematics» more  ISIPTA 1999»
14 years 28 days ago
Coherent Models for Discrete Possibilistic Systems
We consider discrete possibilistic systems for which the available information is given by one-step transition possibilities and initial possibilities. These systems can be repres...
Hugo J. Janssen, Gert De Cooman, Etienne E. Kerre
LCTRTS
2009
Springer
14 years 3 months ago
Eliminating the call stack to save RAM
Most programming languages support a call stack in the programming model and also in the runtime system. We show that for applications targeting low-power embedded microcontroller...
Xuejun Yang, Nathan Cooprider, John Regehr
ECSA
2011
Springer
12 years 8 months ago
Delta-oriented architectural variability using MontiCore
Modeling of software architectures is a fundamental part of software development processes. Reuse of software components and early analysis of software topologies allow the reduct...
Arne Haber, Thomas Kutz, Holger Rendel, Bernhard R...
SEW
2006
IEEE
14 years 2 months ago
Integrating Probability with Time and Shared-Variable Concurrency
Complex software systems typically involve features like time, concurrency and probability, where probabilistic computations play an increasing role. It is challenging to formaliz...
Huibiao Zhu, Shengchao Qin, Jifeng He, Jonathan P....