Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions.
Omri Ben-EliezerDan MikulincerIlias ZadikPublished in: CoRR (2022)
Keyphrases
- high dimensions
- differential privacy
- personal data
- privacy preservation
- high dimensional
- high dimensional data
- privacy preserving
- private data
- personal information
- high dimensional spaces
- privacy preserving data mining
- poor quality
- sliding window
- data distribution
- data privacy
- sensitive information
- privacy protection
- training data
- heavy hitters
- machine learning
- small size
- private information
- third party
- computer vision