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» Adapting RBF Neural Networks to Multi-Instance Learning
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TNN
1998
123views more  TNN 1998»
13 years 7 months ago
A general framework for adaptive processing of data structures
—A structured organization of information is typically required by symbolic processing. On the other hand, most connectionist models assume that data are organized according to r...
Paolo Frasconi, Marco Gori, Alessandro Sperduti
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...
NN
2008
Springer
13 years 6 months ago
Sensory adaptation in human balance control: Lessons for biomimetic robotic bipeds
- This paper describes mechanisms used by humans to stand on moving platforms, such as a bus or ship, and to combine body orientation and motion information from multiple sensors i...
Arash Mahboobin, Patrick J. Loughlin, Mark S. Redf...
IWANN
2009
Springer
14 years 2 months ago
Optimising Machine-Learning-Based Fault Prediction in Foundry Production
Abstract. Microshrinkages are known as probably the most difficult defects to avoid in high-precision foundry. The presence of this failure renders the casting invalid, with the su...
Igor Santos, Javier Nieves, Yoseba K. Penya, Pablo...
IJCNN
2006
IEEE
14 years 1 months ago
TempUnit: A bio-inspired neural network model for signal processing
– We have developed and tested a novel artificial neural network for the processing of temporal signals. The working of the units (TempUnit) is based on the mechanism of temporal...
Olivier F. Manette, Marc A. Maier