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Federated Learning on Transcriptomic Data: Model Quality and Performance Trade-Offs

, , , and . Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part IV, page 279–293. Berlin, Heidelberg, Springer-Verlag, (2024)
DOI: 10.1007/978-3-031-63772-8_26

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A privacy-preserving Federated Learning Approach for kernel methods, , , , and . (2023)Federated learning on transcriptomic data: Model quality and performance trade-offs, , , and . (2024)Federated Learning on Transcriptomic Data: Model Quality and Performance Trade-Offs, , , and . Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part IV, page 279–293. Berlin, Heidelberg, Springer-Verlag, (2024)Is homomorphic encryption feasible for smart mobility?, and . Annals of Computer Science and Information Systems, IEEE, (September 2023)A privacy-preserving framework for collaborative machine learning with kernel methods, , , , and . 2023 5th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA), IEEE, (November 2023)