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» Neural Networks and Complexity Theory
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IJCNN
2006
IEEE
15 years 3 months ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho
BMCBI
2005
126views more  BMCBI 2005»
14 years 9 months ago
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA struc...
Robert G. Beiko, Robert L. Charlebois
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
15 years 2 months ago
Evolution of Goal-Directed Behavior from Limited Information in a Complex Environment
In this paper, we apply an evolutionary algorithm to learning behavior on a novel, interesting task to explore the general issue of learning e ective behaviors in a complex enviro...
Matthew R. Glickman, Katia P. Sycara
JCNS
2010
121views more  JCNS 2010»
14 years 4 months ago
Pattern orthogonalization via channel decorrelation by adaptive networks
The early processing of sensory information by neuronal circuits often includes a reshaping of activity patterns that may facilitate the further processing of stimulus representat...
Stuart D. Wick, Martin T. Wiechert, Rainer W. Frie...
NN
2007
Springer
14 years 9 months ago
Topological relationships between brain and social networks
Brains are complex networks. Previously, we revealed that specific connected structures are either significantly abundant or rare in cortical networks. However, it remains unkno...
Shuzo Sakata, Tetsuo Yamamori