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

• Main Authors: Liu, Ziyao, Guo, Jiale, Yang, Mengmeng, Yang, Wenzhuo, Fan, Jiani, Lam, Kwok-Yan
• Other Authors: School of Computer Science and Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Privacy-Preservation; Knowledge Transfer
• Online Access: https://hdl.handle.net/10356/172524
• Institution: Nanyang Technological University

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...