74 search results - page 7 / 15 » Learning sparse metrics via linear programming |
JMLR
2008
13 years 7 months ago
2008
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
EMNLP
2011
12 years 7 months ago
2011
Log-linear parsing models are often trained by optimizing likelihood, but we would prefer to optimise for a task-specific metric like Fmeasure. Softmax-margin is a convex objecti...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...
TKDE
2011
13 years 2 months ago
2011
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...