-
2
-
-
41549101939
-
Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data
-
O. Banerjee, L. El Ghaoui, and A. d'Aspremont. Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data. Journal of Machine Learning Ressearch, 9:485-516, 2008.
-
(2008)
Journal of Machine Learning Ressearch
, vol.9
, pp. 485-516
-
-
Banerjee, O.1
El Ghaoui, L.2
d'Aspremont, A.3
-
3
-
-
34250698998
-
Convex optimization techniques for fitting sparse Gaussian graphical models
-
O. Banerjee, L. El Ghaoui, A. d'Aspremont, and G. Natsoulis. Convex optimization techniques for fitting sparse Gaussian graphical models. In ICML, pages 89-96, 2006.
-
(2006)
ICML
, pp. 89-96
-
-
Banerjee, O.1
El Ghaoui, L.2
d'Aspremont, A.3
Natsoulis, G.4
-
4
-
-
34247503334
-
Sparse inverse covariance estimates for hyperspectral image classification. Geoscience and Remote Sensing
-
A. Berge, A.C. Jensen, and A.H.S. Solberg. Sparse inverse covariance estimates for hyperspectral image classification. Geoscience and Remote Sensing, IEEE Transactions on, 45(5):1399-1407, 2007.
-
(2007)
IEEE Transactions on
, vol.45
, Issue.5
, pp. 1399-1407
-
-
Berge, A.1
Jensen, A.C.2
Solberg, A.H.S.3
-
5
-
-
0033677172
-
Factored sparse inverse covariance matrices
-
J.A. Bilmes. Factored sparse inverse covariance matrices. In ICASSP, pages 1009-1012, 2000.
-
(2000)
ICASSP
, pp. 1009-1012
-
-
Bilmes, J.A.1
-
6
-
-
47249127654
-
Covariance selection for nonchordal graphs via chordal embedding
-
J. Dahl, L. Vandenberghe, and V. Roychowdhury. Covariance selection for nonchordal graphs via chordal embedding. Optimization Methods Software, 23(4):501-520, 2008.
-
(2008)
Optimization Methods Software
, vol.23
, Issue.4
, pp. 501-520
-
-
Dahl, J.1
Vandenberghe, L.2
Roychowdhury, V.3
-
7
-
-
0142259257
-
Alzheimer's disease as a disconnection syndrome?
-
X. Delbeuck, M. Van der Linden, and F. Collette. Alzheimer's disease as a disconnection syndrome? Neuropsychology Review, 13(2):79-92, 2003.
-
(2003)
Neuropsychology Review
, vol.13
, Issue.2
, pp. 79-92
-
-
Delbeuck, X.1
Van der Linden, M.2
Collette, F.3
-
8
-
-
0001038826
-
Covariance selection
-
A.P. Dempster. Covariance selection. Biometrics, 28(1):157-175, 1972.
-
(1972)
Biometrics
, vol.28
, Issue.1
, pp. 157-175
-
-
Dempster, A.P.1
-
9
-
-
15944399178
-
Sparse graphical models for exploring gene expression data
-
A. Dobra, C. Hans, B. Jones, J. R. Nevins, G. Yao, and M. West. Sparse graphical models for exploring gene expression data. Journal of Multivariate Analysis, 90(1):196-212, 2004.
-
(2004)
Journal of Multivariate Analysis
, vol.90
, Issue.1
, pp. 196-212
-
-
Dobra, A.1
Hans, C.2
Jones, B.3
Nevins, J.R.4
Yao, G.5
West, M.6
-
10
-
-
33744552752
-
For most large underdetermined systems of linear equations, the minimal 11-norm near-solution approximates the sparsest near-solution
-
D.L. Donoho. For most large underdetermined systems of linear equations, the minimal 11-norm near-solution approximates the sparsest near-solution. Communications on Pure and Applied Mathematics, 59(7):907-934, 2006.
-
(2006)
Communications on Pure and Applied Mathematics
, vol.59
, Issue.7
, pp. 907-934
-
-
Donoho, D.L.1
-
11
-
-
0016823810
-
Minimental state: A practical method for grading the cognitive state of patients for the clinician
-
M.F. Folstein, S. Folstein, and P.R. McHugh. Minimental state: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3):189-198, 1975.
-
(1975)
Journal of Psychiatric Research
, vol.12
, Issue.3
, pp. 189-198
-
-
Folstein, M.F.1
Folstein, S.2
McHugh, P.R.3
-
12
-
-
41549108614
-
Sparse inverse covariance estimation with the graphical lasso
-
J. Friedman, T. Hastie, and R. Tibshirani. Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 8(1):1-10, 2007.
-
(2007)
Biostatistics
, vol.8
, Issue.1
, pp. 1-10
-
-
Friedman, J.1
Hastie, T.2
Tibshirani, R.3
-
13
-
-
0038048325
-
Inferring genetic networks and identifying compound mode of action via expression profiling
-
T.S. Gardner, D. di Bernardo, D. Lorenz, and J.J. Collins. Inferring genetic networks and identifying compound mode of action via expression profiling. Science, 301(5629):102-105, 2003.
-
(2003)
Science
, vol.301
, Issue.5629
, pp. 102-105
-
-
Gardner, T.S.1
di Bernardo, D.2
Lorenz, D.3
Collins, J.J.4
-
15
-
-
33644986127
-
Covariance matrix selection and estimation via penalised normal likelihood
-
J.Z. Huang, N. Liu, M. Pourahmadi, and L. Liu. Covariance matrix selection and estimation via penalised normal likelihood. Biometrika, 93(1):85-98, 2006.
-
(2006)
Biometrika
, vol.93
, Issue.1
, pp. 85-98
-
-
Huang, J.Z.1
Liu, N.2
Pourahmadi, M.3
Liu, L.4
-
16
-
-
0004047518
-
-
Oxford University Press, Clarendon
-
S.L. Lauritzen. Graphical models. Oxford University Press, Clarendon, 1996.
-
(1996)
Graphical models
-
-
Lauritzen, S.L.1
-
17
-
-
33645568358
-
Gradient directed regularization for sparse Gaussian concentration graphs, with applications to inference of genetic networks
-
H. Li and J. Gui. Gradient directed regularization for sparse Gaussian concentration graphs, with applications to inference of genetic networks. Biostatistics, 7(2):302-317, 2005.
-
(2005)
Biostatistics
, vol.7
, Issue.2
, pp. 302-317
-
-
Li, H.1
Gui, J.2
-
18
-
-
33947115409
-
Model selection and estimation in the Gaussian graphical model
-
Y. Lin. Model selection and estimation in the Gaussian graphical model. Biometrika, 94(1):19-35, 2007.
-
(2007)
Biometrika
, vol.94
, Issue.1
, pp. 19-35
-
-
Lin, Y.1
-
19
-
-
0021271971
-
Mental and clinical diagnosis of alzheimer's disease: Report of the nincdsadrda work group under the auspices of the department of health and human services task force on alzheimers disease
-
G. McKhann, D. Drachman, and M. Folstein. Mental and clinical diagnosis of alzheimer's disease: report of the nincdsadrda work group under the auspices of the department of health and human services task force on alzheimers disease. Neurology, 34(7):939-944, 1984.
-
(1984)
Neurology
, vol.34
, Issue.7
, pp. 939-944
-
-
McKhann, G.1
Drachman, D.2
Folstein, M.3
-
20
-
-
65449180160
-
The Alzheimer's disease neuroimaging initiative
-
S. Molchan. The Alzheimer's disease neuroimaging initiative. Business Briefing: US Neurology Review, pages 30-32, 2005.
-
(2005)
Business Briefing: US Neurology Review
, pp. 30-32
-
-
Molchan, S.1
-
21
-
-
14944353419
-
Prox-method with rate of convergence o(1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems
-
A. Nemirovski. Prox-method with rate of convergence o(1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems. SIAM Journal on Optimization, 15(1):229-251, 2005.
-
(2005)
SIAM Journal on Optimization
, vol.15
, Issue.1
, pp. 229-251
-
-
Nemirovski, A.1
-
22
-
-
17444406259
-
Smooth minimization of non-smooth functions
-
Y. Nesterov. Smooth minimization of non-smooth functions. Mathematical Programming, 103(1):127-152, 2005.
-
(2005)
Mathematical Programming
, vol.103
, Issue.1
, pp. 127-152
-
-
Nesterov, Y.1
-
23
-
-
33845742477
-
Small-world networks and functional connectivity in Alzheimer's disease
-
C.J. Stam, B.F. Jones, G. Nolte, M. Breakspear, and P. Scheltens. Small-world networks and functional connectivity in Alzheimer's disease. Cereb Cortex, 17:92-99, 2007.
-
(2007)
Cereb Cortex
, vol.17
, pp. 92-99
-
-
Stam, C.J.1
Jones, B.F.2
Nolte, G.3
Breakspear, M.4
Scheltens, P.5
-
24
-
-
46249131887
-
-
K. Supekar, V. Menon, D. Rubin, M. Musen, and M.D. Greicius. Network analysis of intrinsic functional brain connectivity in alzheimer's disease. PLoS Computational Biology, 4(6):e1000100, 2008.
-
K. Supekar, V. Menon, D. Rubin, M. Musen, and M.D. Greicius. Network analysis of intrinsic functional brain connectivity in alzheimer's disease. PLoS Computational Biology, 4(6):e1000100, 2008.
-
-
-
-
25
-
-
0037687416
-
Reverse engineering gene networks: Integrating genetic perturbations with dynamical modeling
-
J. Tegner, M.K. Yeung, J. Hasty, and J.J. Collins. Reverse engineering gene networks: integrating genetic perturbations with dynamical modeling. Proceedings of the National Academy of Sciences, 100(10):5944-5949, 2003.
-
(2003)
Proceedings of the National Academy of Sciences
, vol.100
, Issue.10
, pp. 5944-5949
-
-
Tegner, J.1
Yeung, M.K.2
Hasty, J.3
Collins, J.J.4
-
27
-
-
0035533631
-
Convergence of block coordinate descent method for nondifferentiable maximation
-
P. Tseng. Convergence of block coordinate descent method for nondifferentiable maximation. J. Opt. Theory and Applications, 109(3):474-494, 2001.
-
(2001)
J. Opt. Theory and Applications
, vol.109
, Issue.3
, pp. 474-494
-
-
Tseng, P.1
-
28
-
-
0036322886
-
Automated anatomical labeling of activations in spm using a macroscopic anatomical parcellation of the mni mri single-subject brain
-
N. Tzourio-Mazoyer, B. Landeau, D. Papathanassiou, F. Crivello, O. Etard, N. Delcroix, B. Mazoyer, and M. Joliot. Automated anatomical labeling of activations in spm using a macroscopic anatomical parcellation of the mni mri single-subject brain. NeuroImage, 15(1):273-289, 2002.
-
(2002)
NeuroImage
, vol.15
, Issue.1
, pp. 273-289
-
-
Tzourio-Mazoyer, N.1
Landeau, B.2
Papathanassiou, D.3
Crivello, F.4
Etard, O.5
Delcroix, N.6
Mazoyer, B.7
Joliot, M.8
-
29
-
-
0346848755
-
Fiber tract-based atlas of human white matter anatomy
-
S. Wakana, H. Jiang, L.M. Nagae-Poetscher, P.C. van Zijl, and S. Mori. Fiber tract-based atlas of human white matter anatomy. Radiology, 230(1):77-87, 2004.
-
(2004)
Radiology
, vol.230
, Issue.1
, pp. 77-87
-
-
Wakana, S.1
Jiang, H.2
Nagae-Poetscher, L.M.3
van Zijl, P.C.4
Mori, S.5
-
30
-
-
65449137150
-
Heterogeneous data fusion for Alzheimer's disease study
-
J. Ye, K. Chen, T. Wu, J. Li, Z. Zhao, R. Patel, M. Bae, R. Janardan, H. Liu, G. Alexander, and E. Reiman. Heterogeneous data fusion for Alzheimer's disease study. In KDD, pages 1025-1033, 2008.
-
(2008)
KDD
, pp. 1025-1033
-
-
Ye, J.1
Chen, K.2
Wu, T.3
Li, J.4
Zhao, Z.5
Patel, R.6
Bae, M.7
Janardan, R.8
Liu, H.9
Alexander, G.10
Reiman, E.11
|