Partially-federated learning: A new approach to achieving privacy and effectiveness

Author:

Fisichella Marco,Lax Gianluca,Russo Antonia

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference40 articles.

1. Privacy-preserving data mining: models and algorithms;Aggarwal,2008

2. G. Andrew, O. Thakkar, H.B. McMahan, and S. Ramaswamy. Differentially private learning with adaptive clipping. arXiv preprint arXiv:1905.03871, 2019.

3. A privacy-preserving localization service for assisted living facilities;Buccafurri;IEEE Trans. Serv. Comput.,2016

4. A statistical approach to adult census income level prediction;Chakrabarty,2018

5. A training-integrity privacy-preserving federated learning scheme with trusted execution environment;Chen;Inf. Sci.,2020

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