A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
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...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Abstract. Naive Bayes Nearest Neighbor (NBNN) is a feature-based image classifier that achieves impressive degree of accuracy [1] by exploiting ‘Image-toClass’ distances and b...