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» A Combined Neural and Genetic Learning Algorithm
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115
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GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
15 years 5 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
144
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IEEEPACT
2008
IEEE
15 years 8 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
109
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PRL
1998
93views more  PRL 1998»
15 years 1 months ago
A connectionist method for pattern classification with diverse features
A novel connectionist method is proposed to simultaneously use diverse features in an optimal way for pattern classification. Unlike methods of combining multiple classifiers, a m...
Ke Chen 0001
GI
1998
Springer
15 years 6 months ago
Self-Organizing Data Mining
"KnowledgeMiner" was designed to support the knowledge extraction process on a highly automated level. Implemented are 3 different GMDH-type self-organizing modeling algo...
Frank Lemke, Johann-Adolf Müller
109
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TCSV
2002
132views more  TCSV 2002»
15 years 1 months ago
A study of real-time packet video quality using random neural networks
An important and unsolved problem today is the automatic quantification of the quality of video flows transmitted over packet networks. In particular, the ability to perform this ...
Samir Mohamed, Gerardo Rubino