We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
We propose a classification method based on a decision tree whose nodes consist of linear Support Vector Machines (SVMs). Each node defines a decision hyperplane that classifies p...
—Support Vector Machines are used to combine the outputs of multiple entity extractors, thus creating a composite entity extraction system. The composite system has a significant...
Deborah Duong, James Venuto, Ben Goertzel, Ryan Ri...
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...
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...