In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
The coding of information by neural populations depends critically on the statistical dependencies between neuronal responses. However, there is no simple model that can simultane...
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Abstract: Support vector machines (SVMs) are primarily designed for 2-class classification problems. Although in several papers it is mentioned that the combination of K SVMs can b...