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ISBI
2004
IEEE
14 years 9 months ago
Clustering-Based Framework for Comparing fMRI Analysis Methods
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...
Hamid Soltanian-Zadeh, Gholam-Ali Hossein-Zadeh, A...
NIPS
2004
13 years 10 months ago
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes
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, ...
KDD
2004
ACM
237views Data Mining» more  KDD 2004»
14 years 9 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
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...
Mario Medvedovic, Junhai Guo
PAKDD
2004
ACM
94views Data Mining» more  PAKDD 2004»
14 years 2 months ago
Clustering Multi-represented Objects with Noise
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...
NIPS
2004
13 years 10 months ago
Efficient Out-of-Sample Extension of Dominant-Set Clusters
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...
Massimiliano Pavan, Marcello Pelillo