R. Amadini, M. Gabbrielli, and J. Mauro, An Empirical Evaluation of Portfolios Approaches for Solving CSPs, CPAIOR, 2013.
DOI : 10.1007/978-3-642-38171-3_21
URL : https://hal.archives-ouvertes.fr/hal-00909297

R. Amadini, M. Gabbrielli, and J. Mauro, Features for Building CSP Portfolio Solvers, 2013.

R. Amadini, M. Gabbrielli, and J. Mauro, Abstract, Theory and Practice of Logic Programming, vol.41, issue.4-5, 2014.
DOI : 10.1007/s10601-008-9051-2

R. Amadini, M. Gabbrielli, and J. Mauro, Portfolio Approaches for Constraint Optimization Problems, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01088429

R. Amadini, M. Gabbrielli, and J. Mauro, An enhanced features extractor for a portfolio of constraint solvers, Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC '14, 2014.
DOI : 10.1145/2554850.2555114
URL : https://hal.archives-ouvertes.fr/hal-01089183

S. Arlot and A. Celisse, A survey of cross-validation procedures for model selection, Statistics Surveys, vol.4, issue.0, pp.40-79, 2010.
DOI : 10.1214/09-SS054
URL : https://hal.archives-ouvertes.fr/hal-00407906

G. Audemard, B. Hoessen, S. Jabbour, J. Lagniez, and C. Piette, PeneLoPe, a Parallel Clause-Freezer Solver, SAT Challenge, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00865592

T. Berthold, Measuring the impact of primal heuristics, Operations Research Letters, vol.41, issue.6, pp.611-614, 2013.
DOI : 10.1016/j.orl.2013.08.007

T. Carchrae and J. Beck, Low-knowledge algorithm control, AAAI, pp.49-54, 2004.

C. P. Gomes and B. Selman, Algorithm portfolios, Artificial Intelligence, vol.126, issue.1-2, 2001.
DOI : 10.1016/S0004-3702(00)00081-3

H. Guo and W. H. Hsu, A machine learning approach to algorithm selection for $\mathcal{NP}$ -hard optimization problems: a case study on the MPE problem, Annals of Operations Research, vol.151, issue.3, pp.61-82, 2007.
DOI : 10.1007/s10479-007-0229-6

F. Hutter, L. Xu, H. H. Hoos, and K. Leyton-brown, Algorithm Runtime Prediction: The State of the Art, 1211.

S. Kadioglu, Y. Malitsky, A. Sabharwal, H. Samulowitz, and M. Sellmann, Algorithm Selection and Scheduling, CP, 2011.
DOI : 10.1007/978-3-642-23786-7_35

S. Kadioglu, Y. Malitsky, M. Sellmann, and K. Tierney, ISAC - Instance-Specific Algorithm Configuration, ECAI, 2010.

L. Kotthoff, Algorithm Selection for Combinatorial Search Problems: A Survey. CoRR, abs, 1210.

Y. Malitsky, A. Sabharwal, H. Samulowitz, and M. Sellmann, Boosting Sequential Solver Portfolios: Knowledge Sharing and Accuracy Prediction, pp.153-167, 2013.
DOI : 10.1007/978-3-642-44973-4_17
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.363.7103

E. Omahony, E. Hebrard, A. Holland, C. Nugent, and B. Osullivan, Using case-based reasoning in an algorithm portfolio for constraint solving, AICS, vol.08, 2009.

J. R. Rice, The Algorithm Selection Problem, Advances in Computers, 1976.
DOI : 10.1016/S0065-2458(08)60520-3

K. Smith-miles, Cross-disciplinary perspectives on meta-learning for algorithm selection, ACM Computing Surveys, vol.41, issue.1, 2008.
DOI : 10.1145/1456650.1456656

O. Telelis and P. Stamatopoulos, Combinatorial optimization through statistical instance-based learning, Proceedings 13th IEEE International Conference on Tools with Artificial Intelligence. ICTAI 2001, 2001.
DOI : 10.1109/ICTAI.2001.974466

L. Xu, F. Hutter, H. H. Hoos, and K. Leyton-brown, Hydra-MIP: Automated Algorithm Configuration and Selection for Mixed Integer Programming, RCRA workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, 2011.