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Results: 6
Number of items: 6
  • Open Access
    Allaart, C., Amiri, S., Bal, H., Belloum, A., Gommans, L., Van Halteren, A., & Klous, S. (2025). Private and Secure Distributed Deep Learning: A Survey. ACM Computing Surveys, 57(4), Article 92. https://doi.org/10.1145/3703452
  • Open Access
    Müller, T., Turner, R. J., Amiri, S., Allaart, C., van Binsbergen, L. T., Dijksman, L., van Engers, T., Belloum, A., Grosso, P., Grünwald, P., Hoogoort, K., Härmä, A., Hegeman, J. M., Kassem, J. A., Kebede, M., de Laat, C., van der Nat, P., Pals, A., Scheepers, F., & Klous, S. (2025). Optimizing Clinical Pathways with Federated Data. Jusletter IT, 2025, 147-158. https://doi.org/10.38023/eeb1b383-86b0-4b9e-89d5-57af4b58eeb3
  • Open Access
    Alsayed Kassem, J., Allaart, C., Amiri, S., Kebede, M., Müller, T., Turner, R., Belloum, A., van Binsbergen, L. T., Grunwald, P., van Halteren, A., Grosso, P., de Laat, C., & Klous, S. (2024). Building a Digital Health Twin for Personalized Intervention: The EPI Project. In B. R. Haverkort, A. de Jongste, P. van Kuilenburg, & R. D. Vromans (Eds.), Commit2Data Article 2 (OpenAccess Series in Informatics; Vol. 124). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/OASIcs.Commit2Data.2
  • Open Access
    Yordanov, T. R., Ravelli, A. C. J., Amiri, S., Vis, M., Houterman, S., Van der Voort, S. R., Abu-Hanna, A., & NHR THI Registration Committee (2024). Performance of federated learning-based models in the Dutch TAVI population was comparable to central strategies and outperformed local strategies. Frontiers in Cardiovascular Medicine, 11, Article 1399138. https://doi.org/10.3389/fcvm.2024.1399138
  • Open Access
    Amiri, S., Belloum, A., Nalisnick, E., Klous, S., & Gommans, L. (2022). On the impact of non-IID data on the performance and fairness of differentially private federated learning. In Proceedings, 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshop volume: 27-30 June 2022, Baltimore, Maryland (pp. 52-58). (DSN-W; Vol. 2022). IEEE Computer Society. https://doi.org/10.1109/DSN-W54100.2022.00018
  • Open Access
    Amiri, S., Salimzadeh, S., & Belloum, A. S. Z. (2019). A survey of scalable deep learning frameworks. In IEEE 15th International Conference on eScience: proceedings : 24-27 September 2019, San Diego, California (pp. 650-651). IEEE Computer Society. https://doi.org/10.1109/eScience.2019.00102
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