A. Haury, P. Gestraud, and J. Vert, The Influence of Feature Selection Methods on Accuracy, Stability and Interpretability of Molecular Signatures, PLoS ONE, vol.66, issue.12, 2011.
DOI : 10.1371/journal.pone.0028210.t003

URL : https://hal.archives-ouvertes.fr/hal-00559580

Y. Chevaleyre, F. Koriche, and J. Zucker, Rounding Methods for Discrete Linear Classification, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00771012

J. Wang, Z. Du, R. Payattokool, P. Yu, and C. Chen, A new method to measure the semantic similarity of GO terms, Bioinformatics, vol.23, issue.10, pp.1274-1281, 2007.
DOI : 10.1093/bioinformatics/btm087

N. Dessi, E. Pascariello, and B. Pes, A Comparative Analysis of Biomarker Selection Techniques, BioMed Research International, vol.11, issue.1, 2013.
DOI : 10.1186/1471-2105-11-S1-S5

F. Radlinski, R. Kleinberg, and T. Joachims, Learning diverse rankings with multi-armed bandits, Proceedings of the 25th international conference on Machine learning, ICML '08, 2008.
DOI : 10.1145/1390156.1390255

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.147.3209

E. Delage, Regret-based on-line ranking for a growing digital library, ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 2009.

R. Gaudel and M. Sebag, Feature Selection as a one-player game, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00484049

P. Auer, N. Cesa-bianchi, Y. Freund, and R. Schapire, The Nonstochastic Multiarmed Bandit Problem, SIAM Journal on Computing, vol.32, issue.1, pp.48-77, 2002.
DOI : 10.1137/S0097539701398375

S. Kalyanakrishnan, A. Tewari, P. Auer, and P. Stone, PAC Subset Selection in Stochastic Multi-armed Bandits, 2012.

M. Nowak and R. May, Evolutionary games and spatial chaos, Nature, vol.359, issue.6398, pp.826-829, 1992.
DOI : 10.1038/359826a0

Z. Wang, L. Wang, Z. Yin, and C. Xia, Inferring Reputation Promotes the Evolution of Cooperation in Spatial Social Dilemma Games, PLoS ONE, vol.393, issue.7, 2012.
DOI : 10.1371/journal.pone.0040218.g007

D. Wen-bo, C. Xian-bin, L. Run-ran, and W. Zhen, Effects of Inertia on Evolutionary Prisoner's Dilemma Game, Communications in Theoretical Physics, vol.58, issue.3, 2012.

S. Meloni, A. Buscarino, L. Fortuna, M. Frasca, J. Gómez-gardeñes et al., Effects of mobility in a population of prisoner???s dilemma players, Physical Review E, vol.79, issue.6, 2009.
DOI : 10.1103/PhysRevE.79.067101

H. Zhang, R. Liu, Z. Wang, H. Yang, and B. Wang, Aspiration-induced reconnection in spatial publicgoods game, Europhysics Letters, vol.94, issue.1, p.23275684, 2011.

K. Huang, T. Wang, Y. Cheng, and X. Zheng, Effect of Heterogeneous Investments on the Evolution of Cooperation in Spatial Public Goods Game, PLOS ONE, vol.90, issue.5, 2015.
DOI : 10.1371/journal.pone.0120317.s005

S. Kalyanaraman and C. Umans, Algorithms for Playing Games with Limited Randomness, In: Algorithms ? ESA Lecture Notes in Computer Science, vol.4698, pp.323-334, 2007.
DOI : 10.1007/978-3-540-75520-3_30

S. Flory and O. Teytaud, Upper Confidence Trees with Short Term Partial Information, Procedings of EvoGames 2011, pp.153-162, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00585475

D. Auger, J. Liu, D. Saint-pierre, S. Ruette, and O. Teytaud, Sparse Binary Zero-Sum Games, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01077627

Y. Shoham and K. Leyton-brown, Multiagent Systems. Algorithmic, Game-Theoretic, and Logical Foundations, 2009.

C. Daskalakis, P. Goldberg, and C. Papadimitriou, The complexity of computing a Nash equilibrium, Proceedings of the thirty-eighth annual ACM symposium on Theory of computing, 2006.

J. Robinson, An Iterative Method of Solving a Game, The Annals of Mathematics, vol.54, issue.2, pp.296-301, 1951.
DOI : 10.2307/1969530

M. Grigoriadis and L. Khachiyan, A sublinear-time randomized approximation algorithm for matrix games, Operations Research Letters, vol.18, issue.2, pp.53-58, 1995.
DOI : 10.1016/0167-6377(95)00032-0

J. Audibert and S. Bubeck, Regret bounds and minimax policies under partial monitoring, Journal of Machine Learning Research, vol.11, pp.2635-2686, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00654356

I. Althöfer, On sparse approximations to randomized strategies and convex combinations, Linear Algebra and its Applications, vol.199, 1994.
DOI : 10.1016/0024-3795(94)90357-3

I. Althöfer, On sparse approximations to randomized strategies and convex combinations. Linear Algebra and Its Applications, pp.339-355, 1994.

T. Hofmeister and H. Lefmann, Computing Sparse Approximations Deterministically. Linear Algebra and its Applications, pp.9-19, 1996.
DOI : 10.1016/0024-3795(94)00175-8

URL : http://doi.org/10.1016/0024-3795(94)00175-8

S. Ganzfried, T. Sandholm, and K. Waugh, Strategy Purification, National Conference on Artificial Intelligence: Workshop on Applied Adversarial Reasoning and Risk Modeling (AAAI-AARM), 2011.

S. Ganzfried, T. Sandholm, and K. Waugh, Strategy Purification, 2011.

D. Koller and N. Megiddo, The complexity of two-person zero-sum games in extensive form, Games and Economic Behavior, vol.4, issue.4, pp.528-552, 1992.
DOI : 10.1016/0899-8256(92)90035-Q

D. Koller and N. Megiddo, Fast algorithms for finding randomized strategies in game trees, Proceedings of the twenty-sixth annual ACM symposium on Theory of computing , STOC '94, pp.750-759, 1994.
DOI : 10.1145/195058.195451

D. Koller, Efficient Computation of Equilibria for Extensive Two-Person Games, Games and Economic Behavior, vol.14, issue.2, pp.247-259, 1996.
DOI : 10.1006/game.1996.0051

C. Lemke and J. Howson, Equilibrium Points of Bimatrix Games, Journal of the Society for Industrial and Applied Mathematics, vol.12, issue.2, pp.413-423, 1964.
DOI : 10.1137/0112033

K. Waugh, D. Schnizlein, M. Bowling, and D. Szafron, Abstraction Pathologies in Extensive Games, 2009.

P. Somol and J. Novovi-cová, Evaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.11, pp.1921-1939, 2010.
DOI : 10.1109/TPAMI.2010.34

D. Dernoncourt, B. Hanczar, and J. Zucker, Évolution de la stabilité de la sélection de variables en fonction de la taille d'échantillon et de la dimension, 2012.

A. Cotillard, Dietary intervention impact on gut microbial gene richness, Nature, vol.27, issue.7464, pp.585-588, 2013.
DOI : 10.1038/nature12480

URL : https://hal.archives-ouvertes.fr/hal-01001543

L. Chatelier and E. , Richness of human gut microbiome correlates with metabolic markers Available from, Nature, 2011.

J. Huang, S. Ma, and C. Zhang, Adaptive Lasso for sparse high-dimensional regression models, Statistica Sinica, vol.18, pp.1603-1618, 2008.