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Disambiguation of "Fischer, Lukas"

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Membership Mappings for Practical Secure Distributed Deep Learning

, , , and . IEEE Transactions on Fuzzy Systems, 31 (8): 2617-2631 (August 2023)
DOI: 10.1109/TFUZZ.2023.3235440

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Martin Heinrich Lukas

Kurt Lukas

Martin Lukasiewycz

Rainer Friedrich Wilhelm Lukas

Charlotte Lukas

 

Other publications of authors with the same name

Evaluation of Deep Learning Architectures for Complex Immunofluorescence Nuclear Image Segmentation, , , , , , , , and . IEEE Transactions on Medical Imaging, 40 (7): 1934-1949 (July 2021)Twenty Years of Successful Translational Research: A Case Study of Three COMET Centers., , , , , , and . DEXA Workshops, volume 1633 of Communications in Computer and Information Science, page 155-166. Springer, (2022)Beyond federated learning: On confidentiality-critical machine learning applications in industry., , , , , , , , and . ISM, volume 180 of Procedia Computer Science, page 734-743. Elsevier, (2020)Beyond federated learning: On confidentiality-critical machine learning applications in industry, , , , , , , , and . Procedia Computer Science, (2021)Membership-Mappings for Practical Secure Distributed Deep Learning, , , and . (2022)cite arxiv:2204.05765.Nunc profana tractemus. Detecting Code-Switching in a Large Corpus of 16th Century Letters., , , , , , and . LREC, page 2901-2908. European Language Resources Association, (2022)Secure Federated Learning with Kernel Affine Hull Machines., , and . ESANN, (2023)Towards Practical Secure Privacy-Preserving Machine (Deep) Learning with Distributed Data., , , and . DEXA Workshops, volume 1633 of Communications in Computer and Information Science, page 55-66. Springer, (2022)Beyond federated learning: On confidentiality-critical machine learning applications in industry, , , , , , , , and . Procedia Computer Science, (2021)Proceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2020).Information Theoretic Evaluation of Privacy-Leakage, Interpretability, and Transferability for a Novel Trustworthy AI Framework., , , and . CoRR, (2021)