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» The Tradeoffs of Large Scale Learning
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ECCV
2008
Springer
14 years 10 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
13 years 12 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
BMCBI
2010
193views more  BMCBI 2010»
13 years 3 months ago
Mayday - integrative analytics for expression data
Background: DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the ge...
Florian Battke, Stephan Symons, Kay Nieselt
CVPR
2010
IEEE
14 years 2 months ago
One-Shot Multi-Set Non-rigid Feature-Spatial Matching
We introduce a novel framework for nonrigid feature matching among multiple sets in a way that takes into consideration both the feature descriptor and the features spatial arra...
Marwan Torki and Ahmed Elgammal
ITICSE
2000
ACM
14 years 11 days ago
Pedagogical power tools for teaching Java
We describe a Java toolkit that is designed to support the creation of powerful and extensible GUI interfaces during the first year computer science course. The goals of this tool...
Jeff Raab, Richard Rasala, Viera K. Proulx