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BMCBI
2008
142views more  BMCBI 2008»
14 years 10 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
81
Voted
ML
2010
ACM
119views Machine Learning» more  ML 2010»
14 years 8 months ago
A cooperative coevolutionary algorithm for instance selection for instance-based learning
This paper presents a cooperative evolutionary approach for the problem of instance selection for instance based learning. The presented model takes advantage of one of the most r...
Nicolás García-Pedrajas, Juan Antoni...
77
Voted
ECCC
2010
80views more  ECCC 2010»
14 years 10 months ago
Regret Minimization for Online Buffering Problems Using the Weighted Majority Algorithm
Suppose a decision maker has to purchase a commodity over time with varying prices and demands. In particular, the price per unit might depend on the amount purchased and this pri...
Melanie Winkler, Berthold Vöcking, Sascha Geu...
BMCBI
2010
185views more  BMCBI 2010»
14 years 5 months ago
MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heu
Background: The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most compara...
Raphaël Helaers, Michel C. Milinkovitch
ESA
2001
Springer
105views Algorithms» more  ESA 2001»
15 years 2 months ago
SNPs Problems, Complexity, and Algorithms
Abstract. Single nucleotide polymorphisms (SNPs) are the most frequent form of human genetic variation. They are of fundamental importance for a variety of applications including m...
Giuseppe Lancia, Vineet Bafna, Sorin Istrail, Ross...