We discuss incremental training of support vector machines in which we approximate the regions, where support vector candidates exist, by truncated hypercones. We generate the trun...
Computational comparison is made between two feature selection approaches for nding a separating plane that discriminates between two point sets in an n-dimensional feature space ...
One of the well known risks of large margin training methods, such as boosting and support vector machines (SVMs), is their sensitivity to outliers. These risks are normally mitig...
We propose a distributed parallel support vector machine (DPSVM) training mechanism in a configurable network environment for distributed data mining. The basic idea is to exchange...
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...