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» An Effective Learning Method for Max-Min Neural Networks
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ML
2011
ACM
179views Machine Learning» more  ML 2011»
13 years 3 months ago
Neural networks for relational learning: an experimental comparison
In the last decade, connectionist models have been proposed that can process structured information directly. These methods, which are based on the use of graphs for the representa...
Werner Uwents, Gabriele Monfardini, Hendrik Blocke...

Tutorial
3234views
14 years 3 months ago
Nguyen-Widrow and other Neural Network Weight/Threshold Initialization Methods
Neural networks learn by adjusting numeric values called weights and thresholds. A weight specifies how strong of a connection exists between two neurons. A threshold is a value,...
Jeff Heaton
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
14 years 6 days ago
The baldwin effect in developing neural networks
The Baldwin Effect is a very plausible, but unproven, biological theory concerning the power of learning to accelerate evolution. Simple computational models in the 1980’s gave...
Keith L. Downing
NIPS
1997
13 years 10 months ago
Intrusion Detection with Neural Networks
With the rapid expansion of computer networks during the past few years, security has become a crucial issue for modern computer systems. A good way to detect illegitimate use is ...
Jake Ryan, Meng-Jang Lin, Risto Miikkulainen