In this paper, we first develop a direct Bayesian based Support Vector Machine by combining the Bayesian analysis with the SVM. Unlike traditional SVM-based face recognition metho...
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...
In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...
Background: Predicting the subcellular localization of proteins is important for determining the function of proteins. Previous works focused on predicting protein localization in...
We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the eme...