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» Algebraic Statistics in Model Selection
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GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
13 years 11 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
DAC
2010
ACM
13 years 7 months ago
A correlation-based design space exploration methodology for multi-processor systems-on-chip
Given the increasing complexity of multi-processor systems-onchip, a wide range of parameters must be tuned to find the best trade-offs in terms of the selected system figures of ...
Giovanni Mariani, Aleksandar Brankovic, Gianluca P...
BMCBI
2010
158views more  BMCBI 2010»
13 years 7 months ago
Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing
Background: Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorit...
Corey M. Yanofsky, David R. Bickel
CCR
2008
118views more  CCR 2008»
13 years 7 months ago
A generic language for application-specific flow sampling
Flow records gathered by routers provide valuable coarse-granularity traffic information for several measurement-related network applications. However, due to high volumes of traf...
Harsha V. Madhyastha, Balachander Krishnamurthy
DATAMINE
2006
127views more  DATAMINE 2006»
13 years 7 months ago
Computing LTS Regression for Large Data Sets
Least trimmed squares (LTS) regression is based on the subset of h cases (out of n) whose least squares t possesses the smallest sum of squared residuals. The coverage h may be se...
Peter Rousseeuw, Katrien van Driessen