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A probabilistic support vector machine (PSVM) is proposed for classification of data with uncertainties. Performance of the traditional SVM algorithm is very sensitive to uncertainties. The noises in input space will cause uncertainties of the mapping in feature space. The traditional SVM algorithm may not be effective when uncertainty is large. A new probabilistic optimization is proposed to determine...
We present a method for recognizing individuals from their ldquostyle of actionrdquo. Two forms of human recognition can be useful: the determination that an object is from the class of humans (which is called human detection), and the determination that an object is a particular individual from this class (this is called individual recognition). This paper focuses on the latter problem. A periodicity...
Support vector clustering (SVC) has been successfully applied to solve multi-class classification problems. However, it is usually hard to determine the hyper-parameters of RBF kernel functions. A multiple kernel learning (MKL) algorithm is developed to solve this problem, by which the kernel matrix weights and Lagrange multipliers can be simultaneously obtained with semidefinite programming. However,...
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