SIMONETTO, T. J. A., CORDY, M., GHAMIZI, S., LE TRAON, Y., Lefebvre, C., Boystov, A., & Goujon, A. (2024). On the Impact of Industrial Delays when Mitigating Distribution Drifts: an Empirical Study on Real-world Financial Systems. In KDD Workshop on Discovering Drift Phenomena in Evolving Data Landscape. Springer. Peer reviewed |
GHAMIZI, S., CORDY, M., PAPADAKIS, M., & LE TRAON, Y. (2023). On Evaluating Adversarial Robustness of Chest X-ray Classification. Proceedings of the Workshop on Artificial Intelligence Safety 2023, 3381. Peer reviewed |
GHAMIZI, S., Zhang, J., CORDY, M., PAPADAKIS, M., Sugiyama, M., & LE TRAON, Y. (2023). GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks. Proceedings of the International Conference on Machine Learning (ICML), 202, 11255–11282. Peer reviewed |
DYRMISHI, S., GHAMIZI, S., SIMONETTO, T. J. A., LE TRAON, Y., & CORDY, M. (2023). On the empirical effectiveness of unrealistic adversarial hardening against realistic adversarial attacks. In Conference Proceedings 2023 IEEE Symposium on Security and Privacy (SP) (pp. 1384-1400). IEEE. doi:10.1109/SP46215.2023.00049 Peer reviewed |
DYRMISHI, S., GHAMIZI, S., & CORDY, M. (2023). How do humans perceive adversarial text? A reality check on the validity and naturalness of word-based adversarial attacks. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. Peer reviewed |
GHAMIZI, S. (2022). Multi-objective Robust Machine Learning For Critical Systems With Scarce Data [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52248 |
GHAMIZI, S., GARCIA SANTA CRUZ, B., Temple, P., CORDY, M., Perrouin, G., PAPADAKIS, M., & LE TRAON, Y. (2022). Towards Generalizable Machine Learning for Chest X-ray Diagnosis with Multi-task learning. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/50815. |
GHAMIZI, S., CORDY, M., PAPADAKIS, M., & LE TRAON, Y. (2022). Adversarial Robustness in Multi-Task Learning: Promises and Illusions. In Proceedings of the thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22). doi:10.1609/aaai.v36i1.19950 Peer reviewed |
SIMONETTO, T. J. A., DYRMISHI, S., GHAMIZI, S., CORDY, M., & LE TRAON, Y. (2022). A Unified Framework for Adversarial Attack and Defense in Constrained Feature Space. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22 (pp. 1313-1319). International Joint Conferences on Artificial Intelligence Organization. doi:10.24963/ijcai.2022/183 Peer reviewed |
GHAMIZI, S., CORDY, M., PAPADAKIS, M., & LE TRAON, Y. (2022). On Evaluating Adversarial Robustness of Chest X-ray Classification: Pitfalls and Best Practices. In The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI- 23) - SafeAI Workshop, Washington, D.C., Feb 13-14, 2023. Peer reviewed |
GHAMIZI, S., CORDY, M., PAPADAKIS, M., & LE TRAON, Y. (2021). Evasion Attack STeganography: Turning Vulnerability Of Machine Learning ToAdversarial Attacks Into A Real-world Application. Proceedings of International Conference on Computer Vision 2021. doi:10.1109/ICCVW54120.2021.00010 Peer reviewed |
GHAMIZI, S., CORDY, M., PAPADAKIS, M., & LE TRAON, Y. (2021). Requirements And Threat Models of Adversarial Attacks and Robustness of Chest X-ray classification. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/48411. |
GHAMIZI, S., RWEMALIKA, R., CORDY, M., VEIBER, L., BISSYANDE, T. F. D. A., PAPADAKIS, M., KLEIN, J., & LE TRAON, Y. (2020). Data-driven simulation and optimization for covid-19 exit strategies. In S. GHAMIZI, R. RWEMALIKA, M. CORDY, L. VEIBER, T. F. D. A. BISSYANDE, M. PAPADAKIS, J. KLEIN, ... Y. LE TRAON, Data-driven simulation and optimization for covid-19 exit strategies (pp. 3434-3442). New York, NY, United States: Association for Computing Machinery. doi:10.1145/3394486.3412863 Peer reviewed |
GHAMIZI, S., RWEMALIKA, R., CORDY, M., LE TRAON, Y., & PAPADAKIS, M. (2020). Pandemic Simulation and Forecasting of exit strategies:Convergence of Machine Learning and EpidemiologicalModels. University of Luxembourg. https://orbilu.uni.lu/handle/10993/43166 |
GHAMIZI, S., CORDY, M., GUBRI, M., PAPADAKIS, M., Boystov, A., LE TRAON, Y., & Goujon, A. (2020). Search-based adversarial testing and improvement of constrained credit scoring systems. In ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '20), November 8-13, 2020. Peer reviewed |
GHAMIZI, S., CORDY, M., PAPADAKIS, M., & LE TRAON, Y. (2020). Adversarial Embedding: A robust and elusive Steganography and Watermarking technique [Paper presentation]. IEEE Symposium on Security and Privacy. |
GHAMIZI, S., CORDY, M., PAPADAKIS, M., & LE TRAON, Y. (2020). FeatureNET: Diversity-driven Generation of Deep Learning Models. In International Conference on Software Engineering (ICSE). doi:10.1145/3377812.3382153 Peer reviewed |
GHAMIZI, S., CORDY, M., PAPADAKIS, M., & LE TRAON, Y. (2019). Automated Search for Configurations of Deep Neural Network Architectures. In Automated Search for Configurations of Convolutional Neural Network Architectures. doi:10.1145/3336294.3336306 Peer reviewed |