In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
We propose a Bayesian approach to incorporate anatomical information in the clustering of fiber trajectories. An expectationmaximization (EM) algorithm is used to cluster the traj...
Incremental pattern discovery targets streaming applications where the data continuously arrive incrementally. The questions are how to find patterns (main trends) incrementally; ...
In this paper, a cluster-based framework is introduced for comparing analysis methods of functional magnetic resonance images (fMRI). In the proposed framework, fMRI data is repla...
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...