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A privacy-preserving Federated Learning Approach for kernel methods

A. Hannemann, A. Ünal, A. Swaminathan, E. Buchmann, and M. Akgün. (2023)

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A privacy-preserving framework for collaborative machine learning with kernel methodsA. Hannemann, A. Ünal, A. Swaminathan, E. Buchmann, and M. Akgün. 2023 5th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA), IEEE, (November 2023)IoT Security With INFINITE: The 3-Dimensional Internet Of Things Maturity ModelC. Haar, and E. Buchmann. 2022 9th International Conference on Internet of Things: Systems, Management and Security (IOTSMS), page 1--8. (2022)Online Exams in the Era of ChatGPTE. Buchmann, and A. Thor. 21. Fachtagung Bildungstechnologien (DELFI), Gesellschaft für Informatik e.V., Bonn, (2023)Federated learning on transcriptomic data: Model quality and performance trade-offsA. Hannemann, J. Ewald, L. Seeger, and E. Buchmann. (2024)Federated Learning on Transcriptomic Data: Model Quality and Performance Trade-OffsA. Hannemann, J. Ewald, L. Seeger, and E. Buchmann. Computational Science – ICCS 2024: 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part IV, page 279–293. Berlin, Heidelberg, Springer-Verlag, (2024)Die Entwicklung eines digitalen Praktikums der Cybersicherheit im Bereich Smart HomeE. Buchmann, and V. Jüttner. Tagungsband der 21. Fachtagung Bildungstechnologien der GI Fachgruppe Bildungstechnologien (DELFI 2023), (2023)Is homomorphic encryption feasible for smart mobility?A. Hannemann, and E. Buchmann. Annals of Computer Science and Information Systems, IEEE, (September 2023)Assessing Privacy Policies with AI: Ethical, Legal, and Technical ChallengesI. Aydin, H. Diebel-Fischer, V. Freiberger, J. Möller-Klapperich, E. Buchmann, M. Färber, A. Lauber-Rönsberg, and B. Platow. Proceedings of the 1st International Conference on AI-based Systems and Services (AISyS'24), (2024)ChatSEC - Towards Enhancing Security Vulnerability Reports for Non-ExpertsM. Hoffmann, and E. Buchmann. Proceedings of the 11th Workshop ``Mensch-Maschine-Interaktion in sicherheitskritischen Systemen'' - Mensch und Computer (MuC'24), (2024)Fairness certification for natural Language Processing and Large Language ModelsV. Freiberger, and E. Buchmann. (2024)

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A privacy-preserving Federated Learning Approach for kernel methods

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A privacy-preserving Federated Learning Approach for kernel methods

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A privacy-preserving Federated Learning Approach for kernel methods