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» Algebraic Statistics in Model Selection
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GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
15 years 3 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
14 years 12 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»
14 years 12 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»
14 years 12 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»
14 years 11 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