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- W2068648124 abstract "A support vector machine (SVM) regularized with the Pairwise Elastic Net (PEN) penalty is used to automatically select a sparse set of brain voxel clusters based on the fMRI responses to two stimuli classes. This requires solving the PEN-SVM quadratic program. We show how to design the PEN regularization to encode, in a graph-based fashion, the pairwise similarity structure of the voxel fMRI responses and how to control the spatial locality of the encoding using a voxel searchlight. The voxel similarity encoding is reflected in the sparse structure of the weights of trained PEN-SVM and these weights automatically select a sparse set of voxel clusters. We empirically demonstrate the effectiveness of the approach using a real-world, multi-subject fMRI dataset." @default.
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- W2068648124 date "2013-05-01" @default.
- W2068648124 modified "2023-10-18" @default.
- W2068648124 title "The Pairwise Elastic Net support vector machine for automatic fMRI feature selection" @default.
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- W2068648124 doi "https://doi.org/10.1109/icassp.2013.6637807" @default.
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