Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI

4 Dec 2018Wenwen LiJian LouShuo ZhouHaiping Lu

While functional magnetic resonance imaging (fMRI) is important for healthcare/neuroscience applications, it is challenging to classify or interpret due to its multi-dimensional structure, high dimensionality, and small number of samples available. Recent sparse multilinear regression methods based on tensor are emerging as promising solutions for fMRI, yet existing works rely on unfolding/folding operations and a tensor rank relaxation with limited tightness... (read more)

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