A decentralized power method for PCA with row-wise data partitioning is augmented with Gaussian noise to claim differential privacy; the algorithm and experiments are plausible but the privacy proof is incomplete.
Fed- erated principal component analysis,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Decentralized Differentially Private Power Method
A decentralized power method for PCA with row-wise data partitioning is augmented with Gaussian noise to claim differential privacy; the algorithm and experiments are plausible but the privacy proof is incomplete.