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» Invariances in kernel methods: From samples to objects
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CVPR
2008
IEEE
14 years 11 months ago
Object tracking and detection after occlusion via numerical hybrid local and global mode-seeking
Given an object model and a black-box measure of similarity between the model and candidate targets, we consider visual object tracking as a numerical optimization problem. During...
Zhaozheng Yin, Robert T. Collins
VMV
2001
178views Visualization» more  VMV 2001»
13 years 10 months ago
Consistent Visual Information Processing Applied to Object Recognition Landmark Definition and Real-Time Tracking
The handling of situations where multiple visual information occurs requires the fusion of visual information. This is a very common task found in the processing of multisource / ...
Axel Pinz
NIPS
2007
13 years 10 months ago
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashi...
ICML
2008
IEEE
14 years 9 months ago
Optimized cutting plane algorithm for support vector machines
We have developed a new Linear Support Vector Machine (SVM) training algorithm called OCAS. Its computational effort scales linearly with the sample size. In an extensive empirica...
Sören Sonnenburg, Vojtech Franc
ALT
2005
Springer
14 years 6 months ago
Measuring Statistical Dependence with Hilbert-Schmidt Norms
Abstract. We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate ...
Arthur Gretton, Olivier Bousquet, Alex J. Smola, B...