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...
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
Yee Whye Teh, Michael I. Jordan, Matthew J. Beal, ...
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Abstract. Traditional clustering algorithms are based on one representation space, usually a vector space. However, in a variety of modern applications, multiple representations ex...
Karin Kailing, Hans-Peter Kriegel, Alexey Pryakhin...
Dominant sets are a new graph-theoretic concept that has proven to be relevant in pairwise data clustering problems, such as image segmentation. They generalize the notion of a ma...