Dec 4, 2018 · We perform experiments on four classification problems, including both resting-state fMRI for disease diagnosis and task-based fMRI for neural ...
Oct 10, 2019 · The proposed multilinear regression model (Sturm) performs regression with regularization on the tubal tensor nuclear norm (TNN), demonstrates ...
Dec 4, 2018 · Abstract. While functional magnetic resonance imaging. (fMRI) is important for healthcare/neuroscience applications, it is challenging to ...
In this work, we study t-SVD for sparse multilinear regression and propose a Sparse tubal-regularized multilinear regression (Sturm) method for fMRI.
In this work, we study t-SVD for sparse multilinear regression and propose a Sparse tubal-regularized multilinear regression (Sturm) method for fMRI.
A Sparse tubal-regularized multilinear regression (Sturm) method for fMRI with superior performance of Sturm in classifying fMRI using just a small number ...
Bibliographic details on Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI.
Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J.: Distributed optimization and statistical learning via the alternating direction method of multipliers.
Sturm: Sparse tubal-regularized multilinear regression for fmri. W Li, J Lou, S Zhou, H Lu. International Workshop on Machine Learning in Medical Imaging, 256- ...
