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» Optimal feature selection for support vector machines
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ICML
2008
IEEE
14 years 9 months ago
Modified MMI/MPE: a direct evaluation of the margin in speech recognition
In this paper we show how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to inco...
Georg Heigold, Hermann Ney, Ralf Schlüter, Th...
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
14 years 19 days ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
BMCBI
2007
83views more  BMCBI 2007»
13 years 9 months ago
Identification of sequence motifs significantly associated with antisense activity
Background: Predicting the suppression activity of antisense oligonucleotide sequences is the main goal of the rational design of nucleic acids. To create an effective predictive ...
Kyle A. McQuisten, Andrew S. Peek
CVPR
2010
IEEE
14 years 1 months ago
"Lattice Cut" - Constructing superpixels using layer constraints
Unsupervised over-segmentation of an image into superpixels is a common preprocessing step for image parsing algorithms. Superpixels are used as both regions of support for featur...
Alastair Moore, Simon Prince
IJCNN
2007
IEEE
14 years 3 months ago
On Extending the SMO Algorithm Sub-Problem
—The Support Vector Machine is a widely employed machine learning model due to its repeatedly demonstrated superior generalization performance. The Sequential Minimal Optimizatio...
Christopher Sentelle, Michael Georgiopoulos, Georg...