Lightning: Utility-Driven Anonymization of High-Dimensional Data.
Fabian PrasserRaffael BildJohanna EicherHelmut SpenglerFlorian KohlmayerKlaus A. KuhnPublished in: Trans. Data Priv. (2016)
Keyphrases
- high dimensional data
- dimensionality reduction
- differential privacy
- low dimensional
- high dimensional
- subspace clustering
- nearest neighbor
- high dimensionality
- data points
- high dimensions
- dimension reduction
- data analysis
- privacy preserving
- data distribution
- similarity search
- input space
- clustering high dimensional data
- lower dimensional
- nonlinear dimensionality reduction
- linear discriminant analysis
- data sets
- privacy preservation
- high dimensional spaces
- manifold learning
- original data
- information loss
- variable selection
- high dimensional data sets
- dimensional data
- sparse representation
- high dimensional datasets
- sensitive attributes
- small sample size
- variable weighting
- input data
- decision trees
- computer vision