Efficient dropout-resilient aggregation for privacy-preserving machine learning
Machine learning (ML) has been widely recognized as an enabler of the global trend of digital transformation. With the increasing adoption of data-hungry machine learning algorithms, personal data privacy has emerged as one of the key concerns that could hinder the success of digital transformation....
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Main Authors: | Liu, Ziyao, Guo, Jiale, Lam, Kwok-Yan, Zhao, Jun |
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Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2022
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/162985 |
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Institution: | Nanyang Technological University |
Language: | English |
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