D. V. Arnold, H. Beyer, K. Deb, G. Rudolph, E. Lutton et al., Efficiency and mutation strength adaptation of the (mu/mui,lambda)-es in a noisy environment, PPSN 2000, pp.39-48, 2000.

P. Auer, Using confidence bounds for exploitation-exploration trade-offs, The Journal of Machine Learning Research, vol.3, pp.397-422, 2003.

S. Bernstein, On a modification of chebyshev's inequality and of the error formula of laplace. Original publication, Ann. Sci. Inst. Sav. Ukraine, Sect. Math. 1, vol.3, issue.1, pp.38-49, 1924.

S. Bernstein, The Theory of Probabilities, 1946.

H. Chernoff, A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations, The Annals of Mathematical Statistics, vol.23, issue.4, pp.493-509, 1952.
DOI : 10.1214/aoms/1177729330

B. Denton, Review of " stochastic optimization: Algorithms and applications " by stanislav uryasev and panos m, Interfaces, vol.33, issue.1, pp.100-102, 2003.

L. Devroye, L. Györfi, and G. Lugosi, A probabilistic Theory of Pattern Recognition, 1997.
DOI : 10.1007/978-1-4612-0711-5

J. M. Fitzpatrick and J. J. Grefenstette, Genetic algorithms in noisy environments, Machine Learning, vol.2, issue.2-3, pp.101-120, 1988.
DOI : 10.1007/BF00113893

U. Hammel and T. Bäck, Evolution strategies on noisy functions how to improve convergence properties, PPSN 1994, pp.159-168, 1994.
DOI : 10.1007/3-540-58484-6_260

V. Heidrich-meisner and C. Igel, Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, pp.401-408, 2009.
DOI : 10.1145/1553374.1553426

W. Hoeffding, Probability Inequalities for Sums of Bounded Random Variables, Journal of the American Statistical Association, vol.1, issue.301, pp.13-30, 1963.
DOI : 10.1214/aoms/1177730491

M. Jebalia, A. Auger, G. Rudolph, T. Jansen, S. Lucas et al., On Multiplicative Noise Models for Stochastic Search, PPSN 2008, pp.52-61, 2008.
DOI : 10.1007/978-3-540-87700-4_6
URL : https://hal.archives-ouvertes.fr/inria-00287725

P. Kall, Stochastic Linear Programming, 1976.

K. Marti, Stochastic Optimization Methods, 2005.

V. Mnih, C. Szepesvári, and J. Audibert, Empirical Bernstein stopping, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.672-679, 2008.
DOI : 10.1145/1390156.1390241
URL : https://hal.archives-ouvertes.fr/hal-00834983

P. Rolet and O. Teytaud, Bandit-Based Estimation of Distribution Algorithms for Noisy Optimization: Rigorous Runtime Analysis, 2009.
DOI : 10.1007/978-3-642-13800-3_8
URL : https://hal.archives-ouvertes.fr/inria-00437140

J. K. Sengupta, Stochastic Programming. Methods and Applications, 1972.