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Explicit feature mapping is an appealing way to linearize additive kernels, such as $\chi ^{2}$ kernel for training large-scale support vector machines (SVMs). Although accurate in approximation, feature mapping could pose computational challenges in high-dimensional settings as it expands the original features to a higher dimensional space. To handle this issue in the context of $\chi ^{2}$ kernel...
In this paper, we present a variational Bayes (VB) approach for image segmentation. First, image is modeled by a mixture model, and then with the techniques of factor analyzer, the underlying structure of image content is inferred automatically. Different from the traditional EM algorithm that seriously suffers from component number selection, the proposed method can accurately infer the underlying...
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