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» Optimization on Support Vector Machines
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103
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CVPR
2010
IEEE
15 years 7 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 6 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»
15 years 2 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
129
Voted
BMCBI
2010
227views more  BMCBI 2010»
15 years 3 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
134
Voted
ICIP
2009
IEEE
16 years 4 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...