O. Banerjee, L. Ghaoui, and A. Aspremont, Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data, pp.485-516, 2008.

D. Bickson, Gaussian Belief Propagation: Theory and Application, 2008.

C. Chow and C. Liu, Approximating discrete probability distributions with dependence trees. Information Theory, IEEE Transactions, 1968.
DOI : 10.1109/tit.1968.1054142

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.133.9772

J. Darroch and D. Ratcliff, Generalized Iterative Scaling for Log-Linear Models, The Annals of Mathematical Statistics, vol.43, issue.5, pp.1470-1480, 1972.
DOI : 10.1214/aoms/1177692379

B. Dong and Y. Zhang, An efficient algorithm for l0 minimization in wavelet frame based image restoration, Journal of Scientific Computing, vol.54, issue.2-3, 2012.

J. Fan and R. Li, Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties, Journal of the American Statistical Association, vol.96, issue.456, 2001.
DOI : 10.1198/016214501753382273

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.128.4174

J. Friedman, T. Hastie, and R. Tibshirani, Sparse inverse covariance estimation with the graphical lasso, Biostatistics, vol.9, issue.3, pp.432-441, 2008.
DOI : 10.1093/biostatistics/kxm045

C. Furtlehner, Y. Han, J. M. Lasgouttes, V. Martin, F. Marchal et al., Spatial and temporal analysis of traffic states on large scale networks, 13th International IEEE Conference on Intelligent Transportation Systems, pp.1215-1220, 2010.
DOI : 10.1109/ITSC.2010.5625175

URL : https://hal.archives-ouvertes.fr/hal-00527481

C. Hsieh, M. A. Sustik, I. S. Dhillon, and K. Ravikumar, Sparse inverse covariance matrix estimation using quadratic approximation, p.NIPS, 2011.

A. Jalali, C. C. Johnson, and P. D. Ravikumar, On learning discrete graphical models using greedy methods, pp.1935-1943, 2011.

L. Dicker, B. H. Lin, and X. , Variable selection and estimation with the seamless-L0 penalty models, Statistica Sinica, vol.23, issue.2, pp.929-962, 2012.
DOI : 10.5705/ss.2011.074

D. Malioutov, J. Johnson, and A. Willsky, Walk-sums and Belief Propagation in Gaussian graphical models, pp.2031-2064, 2006.

R. Malouf, A comparison of algorithms for maximum entropy parameter estimation, proceeding of the 6th conference on Natural language learning , COLING-02, pp.49-55, 2002.
DOI : 10.3115/1118853.1118871

J. Pearl, Probabilistic Reasoning in Intelligent Systems: Network of Plausible Inference, 1988.

K. Scheinberg and I. Rish, Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach, pp.ECML-PKDD, 2010.
DOI : 10.1007/978-3-642-15939-8_13

E. Seneta, Non-negative matrices and Markov chains, 2006.
DOI : 10.1007/0-387-32792-4

T. Speed and H. Kiiveri, Gaussian Markov Distributions over Finite Graphs, The Annals of Statistics, vol.14, issue.1, pp.138-150, 1986.
DOI : 10.1214/aos/1176349846

Y. Weiss and W. Freeman, Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology, Neural Computation, vol.13, issue.10, 2001.
DOI : 10.1109/18.910585