We study the problem of learning kernel machines transductively for structured output variables. Transductive learning can be reduced to combinatorial optimization problems over a...
Given a dataset, each element of which labeled by one of k labels, we construct by a very fast algorithm, a k-category proximal support vector machine (PSVM) classifier. Proximal s...
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multi...
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...