Privacy Preserving Feature Selection for Sparse Linear Regression.
Adi AkaviaBen GaliliHayim ShaulMor WeissZohar YakhiniPublished in: Proc. Priv. Enhancing Technol. (2024)
Keyphrases
- privacy preserving
- linear regression
- feature selection
- generalized linear models
- least squares
- privacy preserving data mining
- regression methods
- privacy preservation
- vertically partitioned data
- text categorization
- multi party
- privacy concerns
- data privacy
- private information
- sensitive data
- sparse data
- privacy sensitive
- feature set
- secure multiparty computation
- sensitive information
- classification accuracy
- preserving privacy
- privacy guarantees
- dimensionality reduction
- privacy issues
- horizontally partitioned data
- nonlinear regression
- horizontally partitioned
- naive bayesian classification
- model selection
- high dimensional
- differential privacy
- machine learning
- multi task
- sparse representation
- text classification
- privacy requirements
- support vector
- high dimensionality
- privacy preserving association rule mining
- private data
- knn
- privacy protection
- feature space
- regression model