An algorithmfor data condensation using support vector machines (SVM's)is presented. The algorithm extracts datapoints lying close to the class boundaries,whichform a much re...
We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HMSV...
We apply Support Vector Machines (SVMs) to identify English base phrases (chunks). SVMs are known to achieve high generalization performance even with input data of high dimension...
Abstract. This paper proposes a new support vector machine (SVM) with a robust loss function for data mining. Its dual optimal formation is also constructed. A gradient based algor...
We examine the set covering machine when it uses data-dependent half-spaces for its set of features and bound its generalization error in terms of the number of training errors an...
Mario Marchand, Mohak Shah, John Shawe-Taylor, Mar...