Predictive modelling of online dynamic user-interaction recordings and community identifi cation from such data b ecomes more and more imp ortant w ith th e w idesp read use of on...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Communication latencies within critical sections constitute a major bottleneck in some classes of emerging parallel workloads. In this paper, we argue for the use of Inferentially...
: The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class po...