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» A Kernel Method for the Two-Sample Problem
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TNN
2008
182views more  TNN 2008»
15 years 2 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
121
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PR
2007
293views more  PR 2007»
15 years 1 months ago
Mean shift-based clustering
In this paper, a mean shift-based clustering algorithm is proposed. The mean shift is a kernel-type weighted mean procedure. Herein, we first discuss three classes of Gaussian, C...
Kuo-Lung Wu, Miin-Shen Yang
ICIP
2010
IEEE
15 years 13 days ago
Single image deblurring with adaptive dictionary learning
We propose a motion deblurring algorithm that exploits sparsity constraints of image patches using one single frame. In our formulation, each image patch is encoded with sparse co...
Zhe Hu, Jia-Bin Huang, Ming-Hsuan Yang
133
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GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
15 years 6 months ago
Controlling overfitting with multi-objective support vector machines
Recently, evolutionary computation has been successfully integrated into statistical learning methods. A Support Vector Machine (SVM) using evolution strategies for its optimizati...
Ingo Mierswa
DAGM
2011
Springer
14 years 2 months ago
Using Landmarks as a Deformation Prior for Hybrid Image Registration
Hybrid registration schemes are a powerful alternative to fully automatic registration algorithms. Current methods for hybrid registration either include the landmark information a...
Marcel Lüthi, Christoph Jud, Thomas Vetter