Privacy-Preserving Machine Learning for Collaborative Data Sharing via Auto-encoder Latent Space Embeddings.
Ana María Quintero-OssaJesús SolanoHernán JarcíaDavid ZarrukAlejandro Correa BahnsenCarlos F. ValenciaPublished in: CoRR (2022)
Keyphrases
- data sharing
- latent space
- privacy preserving
- machine learning
- data privacy
- private data
- transfer learning
- homomorphic encryption
- privacy protection
- latent variables
- low dimensional
- data access
- dimensionality reduction
- privacy preservation
- gaussian process
- manifold learning
- differential privacy
- distributed data
- parameter space
- lower dimensional
- data integration
- feature space
- sensitive data
- information sharing
- probabilistic latent semantic analysis
- privacy preserving data mining
- high dimensional
- pattern recognition
- gaussian process latent variable models
- feature selection
- sensitive information
- private information
- peer to peer
- text mining
- active learning
- decision trees
- text classification
- privacy concerns
- data analysis
- model selection
- data mining
- information retrieval
- knowledge discovery
- data sets
- data management
- high dimensional data