K support norm with squared loss function for fMRI analysis.
Matlab
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sparse_k
COPYING.txt
KsparseSquaredLoss.m
README.txt
RunExampleKSupportNorm.m
center.m
normalize.m

README.txt

%%%%%%%%%%%%%%%%%%%%%%%%% LINCENSE %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
KsupportNormFMRICode is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

KsupportNormFMRICode is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with KsupportNormFMRICode. If not, see <http://www.gnu.org/licenses/>.

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% DISCLAIMER %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
KsupportNormFMRICode contains the code with an implementation of the squared 
loss function and the code of ksupport norm package (folder sparse_k) as it
is provided in the webpage :: 
http://www.centrale-ponts.fr/personnel/andreas/code/sparse_k/sparse_k.tar

It was tested in matlab version 2008b and provides no warranties. 

When using the provided KsupportNormFMRICode package for scientific work
please cite the following two papers

1) fMRI Analysis of Cocaine Addiction Using k-support Sparsity.
   Gkirtzou Katerina, Honorio Jean, Samaras Dimitris, Goldstein Rita
   and Blaschko B. Matthew
   International Symposium on Biomedical Imaging (ISBI), 2013.

2) Sparse Prediction with the k-Support Norm 
   Andreas Argyriou, Rina Foygel and Nathan Srebro
   Neural Information Processing Systems (NIPS), 2012