Gaussian Differential Privacy on Riemannian Manifolds.
Yangdi JiangXiaotian ChangYi LiuLei DingLinglong KongBei JiangPublished in: NeurIPS (2023)
Keyphrases
- riemannian manifolds
- differential privacy
- differentially private
- covariance matrices
- euclidean space
- privacy preserving
- vector space
- covariance matrix
- feature space
- maximum likelihood
- mean shift
- privacy preservation
- multi class classification
- geodesic distance
- data sharing
- gaussian distribution
- geometric structure
- parameter space
- gaussian mixture model
- personal information
- manifold learning
- multi class
- reproducing kernel hilbert space
- data privacy
- data integration
- data analysis
- similarity search
- feature vectors
- high dimensional