Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
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...
The high dimensionality of functional magnetic resonance imaging (fMRI) data presents major challenges to fMRI pattern classification. Directly applying standard classifiers often ...
Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef...
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...
The standard language for describing the asymptotic behavior of algorithms is theoretical computational complexity. We propose a method for describing the asymptotic behavior of p...
Simon Goldsmith, Alex Aiken, Daniel Shawcross Wilk...