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» Data Separation by Sparse Representations
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ICIP
2005
IEEE
14 years 3 months ago
Bayesian blind source separation for brain imaging
This paper deals with the problem of blind source separation in fMRI data analysis. Our main contribution is to present a maximum likelihood based method to blindly separate the b...
Hicham Snoussi, Vince D. Calhoun
AAAI
2011
12 years 10 months ago
Sparse Matrix-Variate t Process Blockmodels
We consider the problem of modeling network interactions and identifying latent groups of network nodes. This problem is challenging due to the facts i) that the network nodes are...
Zenglin Xu, Feng Yan, Yuan Qi
CVPR
2005
IEEE
15 years 3 days ago
A Weighted Nearest Mean Classifier for Sparse Subspaces
In this paper we focus on high dimensional data sets for which the number of dimensions is an order of magnitude higher than the number of objects. From a classifier design standp...
Cor J. Veenman, David M. J. Tax
IPMI
2009
Springer
14 years 2 months ago
Discovering Sparse Functional Brain Networks Using Group Replicator Dynamics (GRD)
Functional magnetic resonance imaging (fMRI) has become increasingly used for studying functional integration of the brain. However, the large inter-subject variability in function...
Bernard Ng, Rafeef Abugharbieh, Martin J. McKeown
ICML
2003
IEEE
14 years 11 months ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang