Privacy-enhanced knowledge transfer with collaborative split learning over teacher ensembles

Privacy-enhanced knowledge transfer with collaborative split learning over teacher ensembles

Knowledge Transfer has received much attention for its ability to transfer knowledge, rather than data, from one application task to another. In order to comply with the stringent data privacy regulations, privacy-preserving knowledge transfer is highly desirable. The Private Aggregation of Teacher...

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書目詳細資料
Main Authors:	Liu, Ziyao, Guo, Jiale, Yang, Mengmeng, Yang, Wenzhuo, Fan, Jiani, Lam, Kwok-Yan
其他作者:	School of Computer Science and Engineering
格式:	Conference or Workshop Item
語言:	English
出版:	2023
主題:	Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Privacy-Preservation Knowledge Transfer
在線閱讀:	https://hdl.handle.net/10356/172524
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Nanyang Technological University
語言:	English

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