Gap-free Differentially Private PCA for Gaussian Data
Paper recorded by Signals 4 on 2026-09-25 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-25 on arXiv · recorded by Signals 4 on 2026-09-28
Category: cs.LG · 机器学习 · first seen 2026-09-28
Abstract
We give a gap-free differentially private algorithm for the principal component analysis (PCA) problem with Gaussian data.
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