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Local Differential Privacy

A new method, LDPPPA, offers privacy protection for computing attribute means and user covariance matrices in local differential privacy-preserving principal component analysis, but struggles with attribute heterogeneity.

Featured in No. 73 on 6 Nov 2024 · 1 day after release

Released
5 Nov 2024
First featured
No. 73 · 6 Nov 2024
Published in
Not yet, as far as Semantic Scholar knows
Shares when featured
3
Identifier
SSRN 5009692

Citations and venue from Semantic Scholar (ODC-BY), refreshed weekly. Summary: Quant Letter (CC BY 4.0).

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