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Audet, C., Le Digabel, S., & Tribes, C. (2016). Dynamic scaling in the mesh adaptive direct search algorithm for blackbox optimization. Optimization and Engineering, 17(2), 333-358. Lien externe
Gheribi, A. E., Harvey, J.-P., Bélisle, È., Robelin, C., Chartrand, P., Pelton, A., Bale, C. W., & Le Digabel, S. (2016). Use of a biobjective direct search algorithm in the process design of material science applications. Optimization and Engineering, 17(1), 27-45. Lien externe
Gramacy, R. B., Gray, G. A., Le Digabel, S., Lee, H. K. H., Rajan, P., Wells, G., & Wild, S. M. (2016). Rejoinder. Technometrics, 58(1), 26-29. Lien externe
Gramacy, R. B., Gray, G. A., Le Digabel, S., Lee, H. K. H., Ranjan, P., Wells, G., & Wild, S. M. (2016). Modeling an augmented lagrangian for blackbox constrained optimization. Technometrics, 58(1), 1-11. Lien externe
Amaioua, N., Audet, C., Conn, A. R., & Le Digabel, S. (2016). Efficient solution of quadratically constrained quadratic subproblems within a direct-search algorithm. (Rapport technique n° G-2016-45). Lien externe
Audet, C., Conn, A. R., Le Digabel, S., & Peyrega, M. (2016). A progressive barrier derivative-free trust-region algorithm for constrained optimization. (Rapport technique n° G-2016-49). Lien externe
Audet, C., Ihaddadene, A., Le Digabel, S., & Tribes, C. (2016). Robust optimization of noisy blackbox problems using the Mesh Adaptive Direct Search algorithm. (Rapport technique n° G-2016-55). Lien externe
Audet, C., Le Digabel, S., & Peyrega, M. (2016). A derivative-free trust-region augmented Lagrangian algorithm. (Rapport technique n° G-2016-53). Lien externe
de Sousa, V. J. R., Anjos, M. F., & Le Digabel, S. (2016). Computational study of valid inequalities for the maximum k-cut problem. (Rapport technique n° G-2016-17). Lien externe
Picheny, V., Gramacy, R. B., Wild, S. M., & Le Digabel, S. (2016). Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian. (Rapport technique n° G-2016-43). Lien externe
Talgorn, B., Audet, C., Le Digabel, S., & Kokkolaras, M. (2016). Locally weighted regression models for surrogate-assisted design optimization. (Rapport technique n° G-2016-113). Lien externe
Al-Maskari, S., Belisle, È., Li, X., Le Digabel, S., Nawahda, A., & Zhong, J. (avril 2016). Classification with quantification for air quality monitoring [Communication écrite]. 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2016), Auckland, New Zealand. Lien externe
Gauthier, L., Saunier, N., Le Digabel, S., & Cao, G. (janvier 2016). Calibration of driving behavior models using derivative-free optimization and video data for montreal highways [Communication écrite]. 95th Annual Meeting of the Transportation Research Board, Washington, DC. Lien externe
Picheny, V., Gramacy, R. B., Wild, S., & Le Digabel, S. (décembre 2016). Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian [Communication écrite]. 30th Annual Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain. Lien externe
Amaioua, N., Le Digabel, S., Audet, C., & Conn, A. R. (juin 2016). Efficient solution of quadratically constrained quadratic subproblems within a direct-search algorithm [Affiche]. Workshop on Nonlinear Optimization Algorithms and Industrial Applications, Toronto, Ontario. Non disponible
