S. A. Morales, J. Liu, and O. Teytaud, Noisy optimization convergence rates, In: GECCO (Companion), pp.223-224, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00863584

D. Jones, M. Schonlau, and W. Welch, Efficient global optimization of expensive black-box functions

A. Auger, M. Jebalia, and O. Teytaud, Xse: quasi-random mutations for evolution strategies, Proceedings of Evolutionary Algorithms, 2005.

M. Jebalia, A. Auger, and N. Hansen, Log-Linear Convergence and Divergence of??the??Scale-Invariant (1+1)-ES in Noisy Environments, Algorithmica, vol.13, issue.1, 2010.
DOI : 10.1007/s00453-010-9403-3
URL : https://hal.archives-ouvertes.fr/inria-00433347

D. V. Arnold and H. G. Beyer, A general noise model and its effects on evolution strategy performance, IEEE Transactions on Evolutionary Computation, vol.10, issue.4, pp.380-391, 2006.
DOI : 10.1109/TEVC.2005.859467

S. Finck, H. G. Beyer, and A. Melkozerov, Noisy optimization, Proceedings of the 13th annual conference on Genetic and evolutionary computation, GECCO '11, pp.813-820, 2011.
DOI : 10.1145/2001576.2001688
URL : https://hal.archives-ouvertes.fr/inria-00369466

R. Coulom, CLOP: Confident Local Optimization for Noisy??Black-Box Parameter Tuning, Advances in Computer Games, pp.146-157, 2012.
DOI : 10.1007/978-3-642-31866-5_13
URL : https://hal.archives-ouvertes.fr/hal-00750326

R. Coulom, P. Rolet, N. Sokolovska, and O. Teytaud, Handling expensive optimization with large noise, Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms, FOGA '11, 2011.
DOI : 10.1145/1967654.1967660
URL : https://hal.archives-ouvertes.fr/hal-00517157

O. Teytaud and J. Decock, Noisy Optimization Complexity, FOGA -Foundations of Genetic Algorithms XII -2013, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00755663

H. G. Beyer, The Theory of Evolution Strategies. Natural Computing Series, 2001.

X. Yang, W. Birkfellner, and P. Niederer, Optimized 2d/3d medical image registration using the estimation of multivariate normal algorithm (EMNA), In: Biomedical engineering, 2005.

E. J. Anderson and M. C. Ferris, A Direct Search Algorithm for Optimization with Noisy Function Evaluations, SIAM Journal on Optimization, vol.11, issue.3, pp.837-857, 2001.
DOI : 10.1137/S1052623496312848

S. Lucidi and M. Sciandrone, A derivative-free algorithm for bound constrained optimization, Computational Optimization and Applications, vol.21, issue.2, pp.119-142, 2002.
DOI : 10.1023/A:1013735414984

S. Kim and D. Zhang, Convergence properties of direct search methods for stochastic optimization, Proceedings of the 2010 Winter Simulation Conference, pp.1003-1011, 2010.
DOI : 10.1109/WSC.2010.5679089

N. Hansen, S. Niederberger, L. Guzzella, and P. Koumoutsakos, A Method for Handling Uncertainty in Evolutionary Optimization With an Application to Feedback Control of Combustion, IEEE Transactions on Evolutionary Computation, vol.13, issue.1, pp.180-197, 2009.
DOI : 10.1109/TEVC.2008.924423
URL : https://hal.archives-ouvertes.fr/inria-00276216

J. Villemonteix, E. Vazquez, and E. Walter, An informational approach to the global optimization of expensive-to-evaluate functions, Journal of Global Optimization, vol.10, issue.5, 2008.
DOI : 10.1007/s10898-008-9354-2
URL : https://hal.archives-ouvertes.fr/hal-00354262

V. Fabian, Stochastic Approximation of Minima with Improved Asymptotic Speed, The Annals of Mathematical Statistics, vol.38, issue.1, pp.191-200, 1967.
DOI : 10.1214/aoms/1177699070

P. Rolet and O. Teytaud, Bandit-Based Estimation of Distribution Algorithms for Noisy Optimization: Rigorous Runtime Analysis, Proceedings of Lion4, pp.97-110, 2009.
DOI : 10.1007/978-3-642-13800-3_8
URL : https://hal.archives-ouvertes.fr/inria-00437140

A. Auger, (Convergence results for (1,?)-SA-ES using the theory of ?-irreducible Markov chains

H. Fournier and O. Teytaud, Lower Bounds for Comparison Based Evolution Strategies Using VC-dimension and Sign Patterns, Algorithmica, vol.XVI, issue.2, 2010.
DOI : 10.1007/s00453-010-9391-3
URL : https://hal.archives-ouvertes.fr/inria-00452791