Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
In this paper, we propose a new approach for identifying the language type of character images. We do this by classifying individual character images to determine the language bou...
Abstract. The support vector domain description is a one-class classification method that estimates the shape and extent of the distribution of a data set. This separates the data ...
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...