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BMCBI
2006
187views more  BMCBI 2006»
15 years 6 months ago
Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
Harvey J. Motulsky, Ronald E. Brown
EVOW
2004
Springer
15 years 11 months ago
Evolutionary Search of Thresholds for Robust Feature Set Selection: Application to the Analysis of Microarray Data
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
Carlos Cotta, Christian Sloper, Pablo Moscato
ICASSP
2007
IEEE
15 years 10 months ago
Robust Matched Filters for Target Detection in Hyperspectral Imaging Data
Most detection algorithms for hyperspectral imaging applications assume a target with a perfectly known spectral signature. In practice, the target signature is either imperfectly...
Dimitris Manolakis, Ronald Lockwood, Thomas Cooley...
4OR
2005
104views more  4OR 2005»
15 years 6 months ago
The robust shortest path problem with interval data via Benders decomposition
Many real problems can be modelled as robust shortest path problems on digraphs with interval costs, where intervals represent uncertainty about real costs and a robust path is not...
Roberto Montemanni, Luca Maria Gambardella
SPIESR
1998
239views Database» more  SPIESR 1998»
15 years 7 months ago
Robust Embedded Data from Wavelet Coefficients
An approach to embedding gray scale images using a discrete wavelet transform is proposed. The proposed scheme enables using signature images that could be as much as 25% of the h...
Jong Jin Chae, B. S. Manjunath