Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems. However, SVMs suffer from the catastrophic forgetti...
Ever increasing size of the biomedical literature makes tapping into implicit knowledge in scientific literature a necessity for knowledge discovery. In this paper, a semantic par...
In applications such as character recognition, some classes are heavily overlapped but are not necessarily to be separated. For classification of such overlapping classes, either d...
Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...
We present a new technique that employs support vector machines and Gaussian mixture densities to create a generative/discriminative joint classifier. In the past, several approac...