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» Multiple Kernel Learning with High Order Kernels
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ICCV
2009
IEEE
15 years 20 days ago
Dimensionality Reduction and Principal Surfaces via Kernel Map Manifolds
We present a manifold learning approach to dimensionality reduction that explicitly models the manifold as a mapping from low to high dimensional space. The manifold is represen...
Samuel Gerber, Tolga Tasdizen, Ross Whitaker
ICML
2007
IEEE
14 years 8 months ago
Regression on manifolds using kernel dimension reduction
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...
Jens Nilsson, Fei Sha, Michael I. Jordan
ICMCS
2005
IEEE
182views Multimedia» more  ICMCS 2005»
14 years 1 months ago
An integrated approach for generic object detection using kernel PCA and boosting
In this paper we present a novel framework for generic object class detection by integrating Kernel PCA with AdaBoost. The classifier obtained in this way is invariant to changes...
Saad Ali, Mubarak Shah
PR
2008
90views more  PR 2008»
13 years 7 months ago
Fast computation of geometric moments using a symmetric kernel
This paper presents a novel set of geometric moments with symmetric kernel (SGM) obtained using an appropriate transformation of image coordinates. By using this image transformat...
Chong-Yaw Wee, Paramesran Raveendran, R. Mukundan
CVPR
2010
IEEE
13 years 5 months ago
Visual classification with multi-task joint sparse representation
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
Xiaotong Yuan, Shuicheng Yan