Cited by 14Privacy-Preserving Technologies in DataTensor decomposition and applicationsCryptography and Data Security

Optimized and federated soft-impute for privacy-preserving tensor completion in cyber-physical-social systems

Yang, Jia, Fu, Cai, Lu, Hongwei·2021·Information Sciences

Integrity signals

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Crossref · 10.1016/j.ins.2021.02.028

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53 of 53 references verified0 citation errors · 0 not checkable

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Authors
Yang, J., Fu, C., & Lu, H.
Affiliations
Huazhong University of Science and Technology (CN)
Corresponding author
Fu, Cai
Venue
Information Sciences
Publisher
Elsevier BV
Published
2021-07
Volume
564
Pages
103-123
ISSN
0020-0255 (ISSN-L)
OpenAlex
W3131595479
Cited by
14
References
54
Citations by year
2026: 2 · 2025: 2 · 2024: 3 · 2023: 3 · 2022: 3 · 2021: 1
FWCI
0.88
Type
journal article
Language
en
Open access
closed
Locations
Information Sciences (publishedVersion)
Funders
National Natural Science Foundation of China
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
  • Physical Sciences › Mathematics › Computational Mathematics › Tensor decomposition and applications
  • Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
Keywords
federated learning, differential privacy, cyber-physical-social systems, missing data recovery, privacy-utility trade-off, distributed data

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