Differentially private knowledge transfer for federated learning

T Qi, F Wu, C Wu, L He, Y Huang, X Xie - Nature Communications, 2023 - nature.com
Extracting useful knowledge from big data is important for machine learning. When data is
privacy-sensitive and cannot be directly collected, federated learning is a promising option …

Reconciling the biomedical data commons and the GDPR: three lessons from the EUCAN ELSI collaboratory

A Bernier, F Molnár-Gábor, BM Knoppers… - European Journal of …, 2024 - nature.com
The coming-into-force of the EU General Data Protection Regulation (GDPR) is a watershed
moment in the legal recognition of enforceable rights to informational self-determination. The …

[Retracted] Research on Educational Information Platform Based on Cloud Computing

L Fan, M Xia, P Huang, J Hu - Security and Communication …, 2021 - Wiley Online Library
The traditional method only pays attention to hardware construction and ignores the data
processing steps, which leads to high redundant resource occupancy rate, untimely …

Exchange of human data across international boundaries

HB Bentzen - Annual Review of Biomedical Data Science, 2022 - annualreviews.org
There is a need to share personal data across jurisdictional boundaries. However, the laws
regulating such transfers are not harmonized, and sometimes even conflict, causing …