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KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 10 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
ICDAR
2003
IEEE
14 years 3 months ago
A Flexible Recognition Engine for Complex On-line Handwritten Character Recognition
A major feature of new mobiles terminals using penbased interfaces, such as personal assistants or e-book, is their personal character, implying that a good interface should be ea...
Sanparith Marukatat, Rudy Sicard, Thierry Arti&egr...
ICANN
2010
Springer
13 years 10 months ago
Tumble Tree - Reducing Complexity of the Growing Cells Approach
We propose a data structure that decreases complexity of unsupervised competitive learning algorithms which are based on the growing cells structures approach. The idea is based on...
Hendrik Annuth, Christian-A. Bohn
IJON
2008
118views more  IJON 2008»
13 years 10 months ago
Incremental extreme learning machine with fully complex hidden nodes
Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden nodes, IEEE Trans. Neural Networks 17(4) (2006) 879
Guang-Bin Huang, Ming-Bin Li, Lei Chen, Chee Kheon...
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
14 years 1 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...