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» Support Kernel Machines for Object Recognition
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JMLR
2006
150views more  JMLR 2006»
14 years 9 months ago
Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...
Olvi L. Mangasarian
ISBI
2008
IEEE
15 years 10 months ago
Support vector machine for data on manifolds: An application to image analysis
The Support Vector Machine (SVM) is a powerful tool for classification. We generalize SVM to work with data objects that are naturally understood to be lying on curved manifolds, ...
Suman K. Sen, Mark Foskey, James Stephen Marron, M...
84
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ICML
2010
IEEE
14 years 10 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
CIVR
2007
Springer
126views Image Analysis» more  CIVR 2007»
15 years 3 months ago
Image annotation: which approach for realistic databases?
This paper describes an efficient approach to image annotation. It ranked first on the recent scene categorization track of the ImagEVAL1 benchmark. We show how homogeneous globa...
Nicolas Hervé, Nozha Boujemaa
CVPR
2010
IEEE
15 years 5 months ago
Comparative object similarity for improved recognition with few or no examples
Learning models for recognizing objects with few or no training examples is important, due to the intrinsic longtailed distribution of objects in the real world. In this paper, we...
Gang Wang, David Forsyth, Derek Hoiem