A. Agresti, Categorical Data Analysis, 2013.

J. Bigot, C. Deledalle, and D. Féral, Generalized sure for optimal shrinkage of singular values in low-rank matrix denoising, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01323285

S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers, Machine Learning, pp.1-22, 2011.
DOI : 10.1561/2200000016

J. Cai, E. J. Candès, and Z. Shen, A Singular Value Thresholding Algorithm for Matrix Completion, SIAM Journal on Optimization, vol.20, issue.4, pp.1956-1982, 2010.
DOI : 10.1137/080738970

Y. Cao and Y. Xie, Poisson Matrix Recovery and Completion, IEEE Transactions on Signal Processing, vol.64, issue.6, 2016.
DOI : 10.1109/TSP.2015.2500192

A. Chambolle and T. Pock, A First-Order Primal-Dual Algorithm for Convex Problems with??Applications to Imaging, Journal of Mathematical Imaging and Vision, vol.60, issue.5, pp.120-145, 2011.
DOI : 10.1007/978-3-540-74936-3_22
URL : https://hal.archives-ouvertes.fr/hal-00490826

P. Choler, Consistent Shifts in Alpine Plant Traits along a Mesotopographical Gradient, Arctic, Antarctic, and Alpine Research, vol.37, issue.4, pp.444-4531523, 2005.
DOI : 10.1657/1523-0430(2005)037[0444:CSIAPT]2.0.CO;2
URL : https://hal.archives-ouvertes.fr/halsde-00293865

R. Christensen, Log-Linear Models, 2010.
DOI : 10.1007/978-1-4757-4111-7

M. Collins, S. Dasgupta, and R. E. Schapire, A generalization of principal component analysis to the exponential family, Advances in Neural Information Processing Systems, 2001.

M. A. Davenport, Y. Plan, E. Van-den, M. Berg, and . Wootters, 1-Bit Matrix Completion ArXiv e-prints, 2012.

A. De-falguerolles, Log-Bilinear Biplots in Action, Visualisation of categorical data, pp.527-533, 1998.
DOI : 10.1016/B978-012299045-8/50039-5

J. De and L. , Principal component analysis of binary data by iterated singular value decomposition, Computational Statistics and Data Analysis, vol.50, issue.1, pp.21-39, 2006.

D. L. Donoho and I. M. Johnstone, Ideal spatial adaptation by wavelet shrinkage, Biometrika, vol.81, issue.3, pp.425-455, 1994.
DOI : 10.1093/biomet/81.3.425

B. Efron, Bootstrap methods: another look at the jackknife. The annals of Statistics, pp.1-26, 1979.

A. Feuerverger, Y. He, and S. Khatri, Statistical Significance of the Netflix Challenge, Statistical Science, vol.27, issue.2, pp.202-23111
DOI : 10.1214/11-STS368

A. T. Mário, J. M. Figueiredo, and . Bioucas-dias, Restoration of poissonian images using alternating direction optimization, Trans. Img. Proc, vol.19, issue.12, pp.3133-3145, 2010.

W. Fithian and J. Josse, Multiple correspondence analysis and the multilogit bilinear model, Journal of Multivariate Analysis, vol.157, 2017.
DOI : 10.1016/j.jmva.2017.02.009

J. Friedman, T. Hastie, H. Höfling, and R. Tibshirani, Pathwise coordinate optimization, The Annals of Applied Statistics, vol.1, issue.2, pp.302-33207, 2007.
DOI : 10.1214/07-AOAS131

M. Gavish and D. L. Donoho, Optimal Shrinkage of Singular Values, IEEE Transactions on Information Theory, vol.63, issue.4, 2014.
DOI : 10.1109/TIT.2017.2653801

M. Gavish, L. David, and . Donoho, The optimal hard threshold for singular values is 4/sqrt (3), IEEE Transactions on Information Theory, issue.8, p.60, 2014.

C. Giacobino, S. Sardy, J. Diaz-rodriguez, and N. Hengardner, Quantile universal threshold for model selection, 2016.

R. Glowinski and A. Marrocco, Sur l'approximation, parélémentsparéléments finis d'ordre 1, et la résolution, par pénalisation-dualité, d'une classe deprobì emes de Dirichlet non linéaires, C. R. Acad. Sci. Paris Sér. A, vol.278, pp.1649-1652, 1974.

L. A. Goodman, The Analysis of Cross-Classified Data Having Ordered and/or Unordered Categories: Association Models, Correlation Models, and Asymmetry Models for Contingency Tables With or Without Missing Entries, The Annals of Statistics, vol.13, issue.1, pp.10-69, 1985.
DOI : 10.1214/aos/1176346576

P. Gopalan, F. J. Ruiz, R. Ranganath, and D. Blei, Bayesian nonparametric poisson factorization for recommendation systems, In AISTATS, pp.275-283, 2014.

J. Gower, S. Lubbe, and N. Le-roux, Understanding Biplots, 2011.
DOI : 10.1002/9780470973196

R. Hastie, J. Mazumder, R. Lee, and . Zadeh, Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares. ArXiv e-prints, 2014.

T. Hastie, R. Mazumder, J. Lee, and R. Zadeh, Matrix completion and low-rank svd via fast alternating least squares, Journal in Machine Learning Research, 2015.

T. Jeong, S. Woo, and . Yun, Frame-based Poisson image restoration using a proximal linearized alternating direction method, Inverse Problems, vol.29, issue.7
DOI : 10.1088/0266-5611/29/7/075007

J. Josse and S. Sardy, Adaptive shrinkage of singular values, Statistics and Computing, vol.101, issue.4, pp.1-10, 2015.
DOI : 10.1198/016214506000000735
URL : https://hal.archives-ouvertes.fr/hal-00905708

J. Josse and S. Wager, Bootstrap-based regularization for low-rank matrix estimation, Journal of Machine Learning Research, vol.17, issue.124, pp.1-29, 2016.

M. Kateri, Contingency Table Analysis, 2014.
DOI : 10.1007/978-0-8176-4811-4

O. Klopp, Noisy low-rank matrix completion with general sampling distribution, Bernoulli, vol.20, issue.1, pp.282-303, 2014.
DOI : 10.3150/12-BEJ486
URL : https://hal.archives-ouvertes.fr/hal-00675413

J. Lafond, Low rank matrix completion with exponential family noise, Conference Proceedings, pp.1-18, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01120132

J. Li and D. Tao, Simple exponential family PCA, IEEE Transactions on Neural Networks and Learning Systems, vol.24, issue.3, pp.485-497, 2013.

R. J. Little and D. B. Rubin, Statistical Analysis with Missing Data series in probability and statistics, 1987.

L. T. Liu, E. Dobriban, and A. Singer, epca: High dimensional exponential family pca, 2016.

S. Mohamed, Z. Ghahramani, and K. A. Heller, Bayesian exponential family pca, Advances in Neural Information Processing Systems 21, pp.1089-1096, 2009.

R. Team, R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing

M. Raginsky, R. M. Willett, Z. T. Harmany, and R. F. Marcia, Compressed Sensing Performance Bounds Under Poisson Noise, IEEE Transactions on Signal Processing, vol.58, issue.8, pp.3990-4002, 2010.
DOI : 10.1109/TSP.2010.2049997

J. Salmon, Z. Harmany, C. A. Deledalle, and R. Willett, Poisson Noise Reduction with Non-local PCA, Journal of Mathematical Imaging and Vision, vol.15, issue.2, pp.279-294, 2014.
DOI : 10.1198/106186006X113430
URL : https://hal.archives-ouvertes.fr/hal-00957837

A. Andrey, . Shabalin, B. Andrew, and . Nobel, Reconstruction of a low-rank matrix in the presence of Gaussian noise, Journal of Multivariate Analysis, vol.118, pp.67-76, 2013.

A. B. Tsybakov, Introduction to Nonparametric Estimation, p.9780387790510, 2008.
DOI : 10.1007/b13794

M. Udell, C. Horn, R. Zadeh, and S. Boyd, Generalized low rank models. arXiv preprint, 2014.