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ESANN
2007
15 years 7 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
APCCM
2009
15 years 7 months ago
A Semantic Associative Computation Method for Automatic Decorative-Multimedia Creation with 'Kansei' Information
In the design of multimedia systems, one of the important issues is how to deal with "Kansei" of human beings. The concept of "Kansei" in Japanese includes sev...
Yasushi Kiyoki, Xing Chen
226
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APVIS
2009
15 years 7 months ago
Visualization of signal transduction processes in the crowded environment of the cell
In this paper, we propose a stochastic simulation to model and analyze cellular signal transduction. The high number of objects in a simulation requires advanced visualization tec...
Martin Falk, Michael Klann, Matthias Reuss, Thomas...
147
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BMCBI
2007
126views more  BMCBI 2007»
15 years 6 months ago
Including probe-level uncertainty in model-based gene expression clustering
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
Xuejun Liu, Kevin K. Lin, Bogi Andersen, Magnus Ra...
BMCBI
2006
130views more  BMCBI 2006»
15 years 6 months ago
CARMA: A platform for analyzing microarray datasets that incorporate replicate measures
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
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