Abstract. The support vector machine (SVM) constitutes one of the most successful current learning algorithms with excellent classification accuracy in large real-life problems an...
We introduce a distributed algorithm for solving large scale Support Vector Machines (SVM) problems. The algorithm divides the training set into a number of processing nodes each ...
We present a novel feature screening algorithm by deriving relevance measures from the decision boundary of Support Vector Machines. It alleviates the "independence" assu...
We investigated the geometrical complexity of several high-dimensional, small sample classification problems and its changes due to two popular feature selection procedures, forw...
Erinija Pranckeviciene, TinKam Ho, Ray L. Somorjai
Abstract— While the model parameters of many kernel learning methods are given by the solution of a convex optimisation problem, the selection of good values for the kernel and r...