We introduce several generalizations of classical computer science problems obtained by replacing simpler objective functions with general submodular functions. The new problems i...
ABSTRACT. Estimating a non-uniformly sampled function from a set of learning points is a classical regression problem. Kernel methods have been widely used in this context, but eve...
Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
Abstract—A probabilistic kernel approach to pairwise preference learning based on Gaussian processes is applied to predict preference judgments for sound quality degradation mech...
Perry Groot, Tom Heskes, Tjeerd Dijkstra, James M....
We study a class of algorithms that speed up the training process of support vector machines (SVMs) by returning an approximate SVM. We focus on algorithms that reduce the size of...