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» Optimization on Support Vector Machines
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CVPR
2010
IEEE
15 years 2 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
ICPR
2010
IEEE
15 years 1 months ago
Localized Multiple Kernel Regression
Multiple kernel learning (MKL) uses a weighted combination of kernels where the weight of each kernel is optimized during training. However, MKL assigns the same weight to a kerne...
Mehmet Gönen, Ethem Alpaydin
NPL
2002
168views more  NPL 2002»
14 years 9 months ago
Reduced Rank Kernel Ridge Regression
Ridge regression is a classical statistical technique that attempts to address the bias-variance trade-off in the design of linear regression models. A reformulation of ridge regr...
Gavin C. Cawley, Nicola L. C. Talbot
BMCBI
2010
227views more  BMCBI 2010»
14 years 10 months ago
Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage
Background: HIV-1 targets human cells expressing both the CD4 receptor, which binds the viral envelope glycoprotein gp120, as well as either the CCR5 (R5) or CXCR4 (X4) co-recepto...
Majid Masso, Iosif I. Vaisman
ICIP
2009
IEEE
15 years 11 months ago
Optimum Kernel Function Design From Scale Space Features For Object Detection
Scale-space representation of an image is a significant way to generate features for classification. However, for a specific classification task, the entire scale-space may not be...