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Alimo, R., Sam, D., Lakhmiri, D., Kahovec, B., & Divsalar, D. (2021, March). Automated Data Accountability for Missions in Mars Rover Data [Paper]. IEEE Aerospace Conference (AeroConf 2021), Big Sky, MT, USA (8 pages). External link
Lakhmiri, D., & Le Digabel, S. (2022). Use of Static Surrogates in Hyperparameter Optimization. Operations Research Forum, 3(1). External link
Lakhmiri, D., Alimo, R., & Le Digabel, S. (2022). Anomaly detection for data accountability of Mars telemetry data. Expert Systems With Applications, 189, 116060. External link
Lakhmiri, D. (2021). Optimisation des hyperparamètres des réseaux de neurones profonds [Ph.D. thesis, Polytechnique Montréal]. Available
Lakhmiri, D., Le Digabel, S., & Tribes, C. (2021). HyperNOMAD: Hyperparameter Optimization of Deep Neural Networks Using Mesh Adaptive Direct Search. ACM Transactions on Mathematical Software, 47(3), 1-27. External link
Lakhmiri, D., & Le Digabel, S. (2021). Use of static surrogates in hyperparameter optimization. (Technical Report n° G-2021-10). External link
Lakhmiri, D., Alimo, R., & Le Digabel, S. (2020). Tuning a variational autoencoder for data accountability problem in the Mars Science Laboratory ground data system. (Technical Report n° 2020-31). External link
Lakhmiri, D. (2016). Un environnement pour l'optimisation sans dérivées [Master's thesis, École Polytechnique de Montréal]. Available
