A. Abraham, Extracting Brain Regions from Rest fMRI with Total-Variation Constrained Dictionary Learning, 2013.
DOI : 10.1007/978-3-642-40763-5_75

URL : https://hal.archives-ouvertes.fr/hal-00853242

A. Abraham, Machine learning for neuroimaging with scikit-learn, Frontiers in Neuroinformatics, vol.8, 2014.
DOI : 10.3389/fninf.2014.00014

URL : https://hal.archives-ouvertes.fr/hal-01093971

L. Baldassarre, J. Mourao-miranda, and M. Pontil, Structured Sparsity Models for Brain Decoding from fMRI Data, 2012 Second International Workshop on Pattern Recognition in NeuroImaging
DOI : 10.1109/PRNI.2012.31

A. Beck and M. Teboulle, A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems, SIAM Journal on Imaging Sciences, vol.2, issue.1, 2009.
DOI : 10.1137/080716542

C. F. Beckmann and S. M. Smith, Probabilistic Independent Component Analysis for Functional Magnetic Resonance Imaging, IEEE Transactions on Medical Imaging, vol.23, issue.2, 2004.
DOI : 10.1109/TMI.2003.822821

D. P. Bertsekas, Nonlinear programming, Athena Scientific, 1999.

L. Condat, Fast projection onto the simplex and the 1 ball, In: Math. Program, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01056171

Y. Dai, Fast Algorithms for Projection on an Ellipsoid, SIAM Journal on Optimization, vol.16, issue.4, 2006.
DOI : 10.1137/040613305

E. Dohmatob, Benchmarking solvers for TV-l1 least-squares and logistic regression in brain imaging, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00991743

J. Duchi, Efficient projections onto the l 1-ball for learning in high dimensions, 2008.

D. V. Essen, The Human Connectome Project: A data acquisition perspective, NeuroImage, vol.62, issue.4, 2012.
DOI : 10.1016/j.neuroimage.2012.02.018

K. J. Friston, Statistical parametric maps in functional imaging: A general linear approach, Human Brain Mapping, vol.26, issue.4, 1995.
DOI : 10.1002/hbm.460020402

L. Grosenick, Interpretable whole-brain prediction analysis with GraphNet, NeuroImage, vol.72, p.72, 2013.
DOI : 10.1016/j.neuroimage.2012.12.062

H. Wiki, https://wiki.humanconnectome.org/display/PublicData/HCP+Data+ Dictionary+Public-+500+Subject+Release. Accessed, pp.2010-2019

M. Hebiri and S. Van-de-geer, The Smooth-Lasso and other 1 + 2 -penalized methods, Electron. J. Stat, vol.5, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00462882

D. P. Hibar, Genetic Clustering on the Hippocampal Surface for Genome-Wide Association Studies, 2013.
DOI : 10.1007/978-3-642-40763-5_85

R. Jenatton, G. Obozinski, and F. Bach, Structured sparse principal component analysis, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00414158

A. Mensch, Dictionary Learning for Massive Matrix Factorization, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01308934

R. Saxe, M. Brett, and N. Kanwisher, Divide and conquer: a defense of functional localizers, Neuroimage, vol.30, 2006.

S. M. Smith, Advances in functional and structural MR image analysis and implementation as FSL, NeuroImage, vol.23, 2004.
DOI : 10.1016/j.neuroimage.2004.07.051

E. Varol and C. Davatzikos, Supervised Block Sparse Dictionary Learning for Simultaneous Clustering and Classification in Computational Anatomy, eng. In: Med Image Comput Comput Assist Interv, vol.17, 2014.
DOI : 10.1007/978-3-319-10470-6_56

G. Varoquaux, A group model for stable multi-subject ICA on fMRI datasets, NeuroImage, vol.51, issue.1, p.51, 2010.
DOI : 10.1016/j.neuroimage.2010.02.010

URL : https://hal.archives-ouvertes.fr/hal-00489507

G. Varoquaux, Cohort-Level Brain Mapping: Learning Cognitive Atoms to Single Out Specialized Regions, 2013.
DOI : 10.1007/978-3-642-38868-2_37

URL : https://hal.archives-ouvertes.fr/hal-00841502

G. Varoquaux, FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01247388

G. Varoquaux, Multi-subject Dictionary Learning to Segment an Atlas of Brain Spontaneous Activity, Inf Proc Med Imag, 2011.
DOI : 10.1007/978-3-642-22092-0_46

URL : https://hal.archives-ouvertes.fr/inria-00588898

Y. Ying and D. Zhou, Online Regularized Classification Algorithms, IEEE Transactions on Information Theory, vol.52, issue.11, 2006.
DOI : 10.1109/TIT.2006.883632