S. Bubeck, R. Munos, and G. Stoltz, Pure exploration in finitely-armed and continuous-armed bandits, Theoretical Computer Science, vol.412, issue.19, pp.1832-1852, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00609550

E. J. Candès and B. Recht, Exact matrix completion via convex optimization, Foundations of Computational Mathematics, vol.9, issue.6, pp.717-772, 2009.

E. J. Candès and T. Tao, Near-optimal signal recovery from random projections: universal encoding strategies?, IEEE Transactions on Information Theory, vol.52, issue.12, pp.5406-5425, 2006.

A. Carpentier, O. Klopp, M. Löffler, and R. Nickl, Adaptive confidence sets for matrix completion, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01354030

R. M. Castro and R. D. Nowak, Minimax bounds for active learning, IEEE Transactions on Information Theory, vol.54, issue.5, pp.2339-2353, 2008.

S. Chatterjee, Matrix estimation by universal singular value thresholding, Annals of Statistics, vol.43, issue.1, pp.177-214, 2015.

C. Dhanjal, R. Gaudel, C. , and S. , Online matrix completion through nuclear norm regularisation, Proceedings of the 2014 SIAM International Conference on Data Mining, pp.623-631, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00926605

V. Gabillon, M. Ghavamzadeh, A. Lazaric, and S. Bubeck, Multi-bandit best arm identification, Advances in Neural Information Processing Systems, pp.2222-2230, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00632523

S. Gaïffas and G. Lecué, Sharp oracle inequalities for high-dimensional matrix prediction, IEEE Transactions on Information Theory, vol.57, issue.10, pp.6942-6957, 2011.

E. N. Gilbert, A comparison of signalling alphabets, Bell System Technical Journal, vol.31, issue.3, pp.504-522, 1952.

C. Jin, S. M. Kakade, and P. Netrapalli, Provable efficient online matrix completion via nonconvex stochastic gradient descent, Advances in Neural Information Processing Systems, pp.4520-4528, 2016.

S. Katariya, B. Kveton, C. Szepesvári, C. Vernade, W. et al., Bernoulli rank-1 bandits for click feedback, International Joint Conference on Artificial Intelligence, 2017.
URL : https://hal.archives-ouvertes.fr/hal-02287914

S. Katariya, B. Kveton, C. Szepesvári, C. Vernade, W. et al., Stochastic rank-1 bandits, International Conference on Artificial Intelligence and Statistics, 2017.

O. Klopp, Noisy low-rank matrix completion with general sampling distribution, Bernoulli, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00675413

O. Klopp, Matrix completion by singular value thresholding: Sharp bounds, Electronic journal of statistics, vol.9, issue.2, pp.2348-2369, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01111757

V. Koltchinskii, K. Lounici, and A. B. Tsybakov, Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion, The Annals of Statistics, vol.39, issue.5, pp.2302-2329, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00676868

B. Lois and N. Vaswani, Online Matrix Completion and Online Robust PCA, IEEE International Symposium on Information Theory, 2015.

R. Mazumder, T. Hastie, and R. Tibshirani, Spectral regularization algorithms for learning large incomplete matrices, Journal of machine learning research, vol.11, pp.2287-2322, 2010.

S. Negahban and M. J. Wainwright, Restricted strong convexity and weighted matrix completion: Optimal bounds with noise, Journal of Machine Learning Research, vol.13, pp.1665-1697, 2012.

C. Riquelme, M. Ghavamzadeh, and A. Lazaric, Active learning for accurate estimation of linear models, International Conference on Machine Learning, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01538762

A. Rohde and A. B. Tsybakov, Estimation of high-dimensional low-rank matrices, Annals of Statistics, vol.39, issue.2, pp.887-930, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00606063

A. B. Tsybakov, Introduction to Nonparametric Estimation. Springer Series in Statistics, 2009.

R. R. Varshamov, Estimate of the number of signals in error correcting codes, Doklady Akademii Nauk SSSR, vol.117, pp.739-741, 1957.

M. Wedel and W. A. Kamakura, Market segmentation : Conceptual and methodological foundations, 2000.