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» A Minimax Method for Learning Functional Networks
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SAB
2010
Springer
117views Optimization» more  SAB 2010»
13 years 6 months ago
Indirectly Encoding Neural Plasticity as a Pattern of Local Rules
Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
Sebastian Risi, Kenneth O. Stanley
JSAC
2010
138views more  JSAC 2010»
13 years 6 months ago
Dynamic conjectures in random access networks using bio-inspired learning
—Inspired by the biological entities’ ability to achieve reciprocity in the course of evolution, this paper considers a conjecture-based distributed learning approach that enab...
Yi Su, Mihaela van der Schaar
WSOM
2009
Springer
14 years 2 months ago
Incremental Figure-Ground Segmentation Using Localized Adaptive Metrics in LVQ
Vector quantization methods are confronted with a model selection problem, namely the number of prototypical feature representatives to model each class. In this paper we present a...
Alexander Denecke, Heiko Wersing, Jochen J. Steil,...
ICPR
2004
IEEE
14 years 8 months ago
Neural Network-Based Proper Names Extraction in Fax Images
In this paper, we are interested in the sender's name extraction in fax cover pages through a machine learning scheme. For this purpose, two analysis methods are implemented ...
Laurence Likforman-Sulem, Noura Azzabou
FGCN
2008
IEEE
175views Communications» more  FGCN 2008»
14 years 2 months ago
Environment Recognition Based on Human Actions Using Probability Networks
To realize context aware applications for smart home environments, it is necessary to recognize function or usage of objects as well as categories of them. On conventional researc...
Hiroshi Miki, Atsuhiro Kojima, Koichi Kise