FedAUXfdp: Differentially private one-shot federated distillation

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Titel FedAUXfdp: Differentially private one-shot federated distillation
Medien Goebel, R., Yu, H., Faltings, B., Fan, L., Xiong, Z. (eds) Trustworthy Federated Learning. FL 2022. Lecture Notes in Computer Science.
Verlag Springer
Band 13448
Verfasser Haley Hoech, Prof. Dr. Roman Rischke, Karsten Müller, Wojciech Samek
Seiten 100-114
Veröffentlichungsdatum 29.03.2023
Zitation Hoech, Haley; Rischke, Roman; Müller, Karsten; Samek, Wojciech (2023): FedAUXfdp: Differentially private one-shot federated distillation. Goebel, R., Yu, H., Faltings, B., Fan, L., Xiong, Z. (eds) Trustworthy Federated Learning. FL 2022. Lecture Notes in Computer Science. 13448, 100-114.