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» Using Machine Learning to Focus Iterative Optimization
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JMLR
2010
162views more  JMLR 2010»
14 years 9 months ago
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design
An exceedingly large number of scientific and engineering fields are confronted with the need for computer simulations to study complex, real world phenomena or solve challenging ...
Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom D...
128
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BMCBI
2007
166views more  BMCBI 2007»
15 years 3 months ago
Optimization of filtering criterion for SEQUEST database searching to improve proteome coverage in shotgun proteomics
Background: In proteomic analysis, MS/MS spectra acquired by mass spectrometer are assigned to peptides by database searching algorithms such as SEQUEST. The assignations of pepti...
Xinning Jiang, Xiaogang Jiang, Guanghui Han, Mingl...
IJRR
2008
139views more  IJRR 2008»
15 years 2 months ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal
GECCO
2006
Springer
151views Optimization» more  GECCO 2006»
15 years 6 months ago
Sporadic model building for efficiency enhancement of hierarchical BOA
This paper describes and analyzes sporadic model building, which can be used to enhance the efficiency of the hierarchical Bayesian optimization algorithm (hBOA) and other advance...
Martin Pelikan, Kumara Sastry, David E. Goldberg
PROMISE
2010
14 years 9 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies