C. Malherbe, N. Vayatis. 
A ranking approach to global optimization.
Journal version. Submitted, 2017.

Cédric Malherbe, Nicolas Vayatis:
Global optimization of Lipschitz functions.
Proceedings of ICML 2017: 2314-2323, 2017.

D. Sarkar, E. Contal, N. Vayatis, F. Dias.
Prediction and optimization of wave energy converter arrays using a machine learning approach.
Renewable Energy, Vol.97:504-517, 2016.

C. Malherbe, E. Contal, N. Vayatis.
A Ranking Approach to Global Optimization.
Proceedings of ICML'16, 2016.

Emile Contal, Cédric Malherbe, Nicolas Vayatis.
Optimization for Gaussian Processes via Chaining.
NIPS workshop “Bayesian Optimization: Scalability and Flexibility”, NIPS'15, 2015.

Emile Contal, Vianney Perchet, Nicolas Vayatis.
Gaussian Process Optimization with Mutual Information.
Proceedings of ICML'14 and JMLR W&CP 32 (1) : 253–261, 2014.

A. Juditsky, A. Nazin, A. Tsybakov, and N. Vayatis.
Gap-free bounds for stochastic multi-armed bandit.
Proceedings of IFAC'08 , Seoul, Korea, 2007, 2007.

A. Juditsky, A. Nazin, A. Tsybakov, and N. Vayatis.
Recursive Aggregation of Estimators via the  Mirror Descent Algorithm with averaging.
Problems of Information Transmission ,  41(4): 368-384, 2005.

A. Juditsky, A. Nazin, A. Tsybakov and N. Vayatis.
Generalization Error Bounds for Aggregation by Mirror Descent With Averaging.
Proceedings of Neural Information Processing Systems NIPS'2005 , MIT Press, 2005.