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138
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CEC
2010
IEEE
15 years 3 months ago
An analysis of massively distributed evolutionary algorithms
Computational science is placing new demands on optimization algorithms as the size of data sets and the computational complexity of scientific models continue to increase. As thes...
Travis J. Desell, David P. Anderson, Malik Magdon-...
140
Voted
ICA
2010
Springer
15 years 3 months ago
Binary Sparse Coding
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
Marc Henniges, Gervasio Puertas, Jörg Bornsch...
DATAMINE
2008
143views more  DATAMINE 2008»
15 years 2 months ago
Automatically countering imbalance and its empirical relationship to cost
Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...
JCB
2006
140views more  JCB 2006»
15 years 2 months ago
HAPLOFREQ-Estimating Haplotype Frequencies Efficiently
A commonly used tool in disease association studies is the search for discrepancies between the haplotype distribution in the case and control populations. In order to find this d...
Eran Halperin, Elad Hazan
167
Voted
SOCO
2010
Springer
15 years 26 days ago
Automatic detection of trends in time-stamped sequences: an evolutionary approach
This paper presents an evolutionary algorithm for modeling the arrival dates in time-stamped data sequences such as newscasts, e-mails, IRC conversations, scientific journal artic...
Lourdes Araujo, Juan Julián Merelo Guerv&oa...
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