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Bonami, P., Lodi, A., & Zarpellon, G. (2022). A classifier to decide on the linearization of mixed-integer quadratic problems in CPLEX. Operations Research, 70(6), 3303-3320. Lien externe
Zarpellon, G., Jo, J., Lodi, A., & Bengio, Y. (février 2021). Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies [Communication écrite]. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence. Publié dans Proceedings of the ... AAAI Conference on Artificial Intelligence, 35(5). Lien externe
Zarpellon, G. (2020). Machine learning algorithms in Mixed-Integer Programming [Thèse de doctorat, Polytechnique Montréal]. Disponible
Fischetti, M., Lodi, A., & Zarpellon, G. (juin 2019). Learning MILP Resolution Outcomes Before Reaching Time-Limit [Communication écrite]. 16th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2019), Thessaloniki, Greece. Lien externe
Bonami, P., Lodi, A., & Zarpellon, G. (juin 2018). Learning a classification of mixed-integer quadratic programming problems [Communication écrite]. 15th International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2018), Delft, Netherlands. Lien externe
Fischetti, M., Lodi, A., & Zarpellon, G. (2018). Learning milp resolution outcomes before reaching time-limit. (Rapport technique n° DS4DM-2018-009). Lien externe
Lodi, A., & Zarpellon, G. (2017). On learning and branching: A survey. (Rapport technique n° DS4DM-2017-004). Lien externe
