Benchmarking solvers for TV-ℓ1 least-squares and logistic regression in brain imaging

Proceedings - 2014 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014

Volumn , Issue , 2014, Pages

  Dohmatob, Elvis Dopgima ^a   Gramfort, Alexandre ^a,b   Thirion, Bertrand ^a   Varoquaux, Gael ^a  

^a INRIA   (France)

^b INSERM U562 CEA / DSV / I2BM / Neurospin / Unicog ^*  (France)

Author keywords

classification; fMRI; non smooth convex optimization; regression; sparse models; Total Variation

Indexed keywords

BRAIN MAPPING; CLASSIFICATION (OF INFORMATION); CONVEX OPTIMIZATION; IMAGE DENOISING; MAGNETIC RESONANCE IMAGING; OPTIMIZATION; PATTERN RECOGNITION; PRASEODYMIUM ALLOYS;

FMRI; NON-SMOOTH CONVEX OPTIMIZATIONS; REGRESSION; SPARSE MODELS; TOTAL VARIATION;

NEUROIMAGING;

EID: 84905734628     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PRNI.2014.6858516     Document Type: Conference Paper

References (26)

1. J. V. Haxby, M. I. Gobbini, M. L. Furey, A. Ishai, J. L. Schouten, and P. Pietrini, "Distributed and Overlapping Representations of Faces and Objects in Ventral Temporal Cortex,"Science, vol. 293, p. 2425, 2001
2. Y. Kamitani and F. Tong, "Decoding the visual and subjective contents of the human brain,"Nat. Neurosci., vol. 8, p. 679, 2005
3. J.-D. Haynes and G. Rees, "Decoding mental states from brain activity in humans,"Nat. Rev. Neurosci., vol. 7, p. 523, 2006
4. Y. Fan, N. Batmanghelich, C. M. Clark, and C. Davatzikos, "Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline,"Neuroimage, vol. 39, p. 1731, 2008
5. M. K. Carroll, G. A. Cecchi, I. Rish, R. Garg, and A. R. Rao, "Prediction and interpretation of distributed neural activity with sparse models,"NeuroImage, vol. 44, p. 112, 2009
6. V. Michel, A. Gramfort, G. Varoquaux, E. Eger, and B. Thirion, "Total variation regularization for fMRI-based prediction of behaviour,"IEEE Transactions on Medical Imaging, vol. 30, p. 1328, 2011
7. L. Baldassarre, J. Mourao-Miranda, and M. Pontil, "Structured sparsity models for brain decoding from fMRI data,"in PRNI, 2012, p. 5
8. A. Gramfort, B. Thirion, and G. Varoquaux, "Identifying predictive regions from fMRI with TV-L1 prior,"in PRNI, 2013
9. A. Abraham, E. Dohmatob, B. Thirion, D. Samaras, and G. Varoquaux, "Extracting brain regions from rest fMRI with total-variation constrained dictionary learning,"MICCAI, 2013
10. I. Daubechies, M. Defrise, and C. De Mol, "An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,"Commun. Pure Appl. Math., vol. 57, no. 11, pp. 1413-1457, 2004
11. A. Beck and M. Teboulle, "A fast iterative shrinkage-thresholding algorithm for linear inverse problems,"SIAM Journal on Imaging Sciences, vol. 2, p. 183, 2009
12. J. A. Suykens, T. Van Gestel, J. De Brabanter, B. De Moor, and J. Vandewalle, Least squares support vector machines. World Scientific, 2002
13. A. Beck and M. Teboulle, "Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems,"Trans. Img. Proc., vol. 18, p. 2419, 2009
14. C.-J. L. Guo-Xun Yuan, Chia-Hua Ho, "An improved glmnet for l1-regularized logistic regression,"Department of Computer Science National Taiwan University, 2012
15. S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, "Distributed optimization and statistical learning via the alternating direction method of multipliers,"Fundations and Trends in Machine Learning, 2010
16. A. Chambolle and T. Pock, "A first-order primal-dual algorithm for convex problems with applications to imaging,"J. Math. Imaging Vis., vol. 40, p. 120, 2011
17. A. Lewis and M. Overton, "Nonsmooth optimization via BFGS,"2008
18. J. Burke, A. Lewis, and M. Overton, "A robust gradient sampling algorithm for nonsmooth, nonconvex optimization,"SIAM J. Optimization, vol. 15, pp. 751-779, 2005
19. J. Bobin, S. Becker, and E. Candes, "A fast and accurate first-order method for sparse recovery,"SIAM J Imaging Sciences, 2011
20. Y. Nesterov, "Smooth minimization of non-smooth functions, "Math. Program., vol. Ser. A 103, p. 127152, 2005
21. Y. Nesterov, "Excessive gap technique in nonsmooth convex minimization,"SIAM Journal on Optimization, vol. 16, p. 235, 2005
22. A. Beck and M. Teboulle, "Smoothing and first order methods: A unified framework,"SIAM J. OPTIM., vol. 22, no. 2, pp. 557-580, 2012
23. C. Zhu, R. H. Byrd, P. Lu, and J. Nocedal, "L-BFGS-B-Fortran subroutines for large-scale bound constrained optimization,"NORTHWESTERN UNIVERSITY Department of Electrical Engineering and Computer Science, 1994
24. Y. Nesterov, "A method of solving a convex programming problem with convergence rate O(1/k2),"Soviet Mathematics Doklady, 1983
25. S. M. Tom, C. R. Fox, C. Trepe, and R. A. Poldrack, "The neural basis of loss aversion in decision-making under risk,"Science, vol. 315, no. 5811, pp. 515-518, 2007
26. K. Jimura and R. A. Poldrack, "Analyses of regional-Average activation and multivoxel pattern information tell complementary stories,"Neuropsychologia, vol. 50, p. 544, 2012.