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» Combining Multiple Kernels by Augmenting the Kernel Matrix
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DAGM
2011
Springer
13 years 11 months ago
Relaxed Exponential Kernels for Unsupervised Learning
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
97
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PR
2008
144views more  PR 2008»
14 years 11 months ago
Kernel quadratic discriminant analysis for small sample size problem
It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...
Jie Wang, Konstantinos N. Plataniotis, Juwei Lu, A...
CVPR
2004
IEEE
16 years 1 months ago
Multiple Kernel Tracking with SSD
Kernel-based objective functions optimized using the mean shift algorithm have been demonstrated as an effective means of tracking in video sequences. The resulting algorithms com...
Gregory D. Hager, Maneesh Dewan, Charles V. Stewar...
ICPR
2010
IEEE
15 years 6 months ago
Object Recognition and Localization Via Spatial Instance Embedding
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
Nazli Ikizler Cinbis, Stan Sclaroff
DAGM
2008
Springer
15 years 1 months ago
A Multiple Kernel Learning Approach to Joint Multi-class Object Detection
Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an imag...
Christoph H. Lampert, Matthew B. Blaschko