O. Filippi and A. Cappécapp´cappé, Garivier and C. SzepesváriSzepesv´Szepesvári Parametric Bandits: The Generalized Linear Case

D. Gelly and . Silver, Combining online and offline knowledge in UCT, Proceedings of the 24th international conference on Machine learning, ICML '07, p.7
DOI : 10.1145/1273496.1273531

URL : https://hal.archives-ouvertes.fr/inria-00164003

L. Giordana, Saitta Phase Transitions in Relational Learning, Mach. Learn, p.0

L. A. Kira, Rendell A practical approach to feature selection, p.92

C. Kocsis, SzepesváriSzepesv´Szepesvári Bandit based Monte-Carlo planning, p.6

S. Melo, Meyn, and I. Ribeiro An Analysis of Reinforcement Learning with Function Approximation, p.8

F. De-mesmay, A. Rimmel, Y. Voronenko, and M. , P ¨ uschel Bandit-based optimization on graphs with application to library performance tuning, p.9

M. Neal, J. Zhang, and . Chap, High Dimensional Classification with Bayesian Neural Networks and Dirichlet Diffusion Trees. Feature extraction, foundations and applications, 2006.

S. R. Rogers, Gunn Identifying feature relevance using a Random Forest, p.5

M. Rolet and O. Sebag, Teytaud Boosting Active Learning to optimality: a tractable Monte-Carlo, Billiard-based algorithm, p.9

Q. Shen, C. J. Ong, X. P. Li, and E. P. , Wilder-Smith Feature selection via sensitivity analysis of SVM probabilistic outputs, Mach. Learn, p.8