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GRC
2010
IEEE
15 years 7 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
AROBOTS
2008
177views more  AROBOTS 2008»
15 years 6 months ago
Controlling swimming and crawling in a fish robot using a central pattern generator
Online trajectory generation for robots with multiple degrees of freedom is still a difficult and unsolved problem, in particular for non-steady state locomotion, that is, when th...
Alessandro Crespi, Daisy Lachat, Ariane Pasquier, ...
BMCBI
2008
128views more  BMCBI 2008»
15 years 6 months ago
Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sa
Background: In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a sign...
Cornelia Frömke, Ludwig A. Hothorn, Siegfried...
BMCBI
2007
134views more  BMCBI 2007»
15 years 6 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
BMCBI
2008
139views more  BMCBI 2008»
15 years 6 months ago
The C1C2: A framework for simultaneous model selection and assessment
Background: There has been recent concern regarding the inability of predictive modeling approaches to generalize to new data. Some of the problems can be attributed to improper m...
Martin Eklund, Ola Spjuth, Jarl E. S. Wikberg