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TON
2010
126views more  TON 2010»
13 years 2 months ago
MAC Scheduling With Low Overheads by Learning Neighborhood Contention Patterns
Aggregate traffic loads and topology in multi-hop wireless networks may vary slowly, permitting MAC protocols to `learn' how to spatially coordinate and adapt contention patte...
Yung Yi, Gustavo de Veciana, Sanjay Shakkottai
CEC
2010
IEEE
13 years 8 months ago
A hormone-based controller for evolutionary multi-modular robotics: From single modules to gait learning
For any embodied, mobile, autonomous agent it is essential to control its actuators appropriately for the faced task. This holds for natural organisms as well as for robots. If sev...
Heiko Hamann, Jürgen Stradner, Thomas Schmick...
PAMI
2006
178views more  PAMI 2006»
13 years 7 months ago
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models
Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. I...
Jakob J. Verbeek
IJRR
2011
126views more  IJRR 2011»
13 years 2 months ago
Optimization and learning for rough terrain legged locomotion
We present a novel approach to legged locomotion over rough terrain that is thoroughly rooted in optimization. This approach relies on a hierarchy of fast, anytime algorithms to p...
Matthew Zucker, Nathan D. Ratliff, Martin Stolle, ...
ECCV
2010
Springer
14 years 2 days ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...