In the conventional incremental training of support vector machines, candidates for support vectors tend to be deleted if the separating hyperplane rotates as the training data ar...
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
In recent years, research and development in the field of machine learning and classification techniques have gained paramount importance. The future generation of intelligent e...
– The visualization of support vector machines in realistic settings is a difficult problem due to the high dimensionality of the typical datasets involved. However, such visuali...
Recent efforts aimed at improving the scalability of the JavaTM platform have focused primarily on the safe collocation of multiple applications in the virtual machine. This is of...