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GHAMIZI Salah

Main Referenced Co-authors
CORDY, Maxime  (16)
LE TRAON, Yves  (15)
PAPADAKIS, Michail  (13)
DYRMISHI, Salijona  (3)
RWEMALIKA, Renaud  (2)
Main Referenced Keywords
Deep Learning (2); Machine Learning (2); Robustness (2); Steganography (2); Watermarking (2);
Main Referenced Unit & Research Centers
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Security Design and Validation Research Group (SerVal) (3)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Other (2)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) (1)
ULHPC - University of Luxembourg: High Performance Computing (1)
Main Referenced Disciplines
Computer science (17)
Radiology, nuclear medicine & imaging (1)

Publications (total 17)

The most downloaded
373 downloads
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://hdl.handle.net/10993/43166

The most cited

26 citations (Scopus®)

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 https://hdl.handle.net/10993/45706

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., 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

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. (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.

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. (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

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., 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., 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.

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., 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. (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

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