Federated Learning and Privacy: Building privacy-preserving systems for machine learning and data science on decentralized data.
Kallista A. BonawitzPeter KairouzBrendan McMahanDaniel RamagePublished in: ACM Queue (2021)
Keyphrases
- privacy preserving
- data privacy
- private data
- privacy requirements
- sensitive information
- privacy sensitive
- private information
- preserving privacy
- sensitive data
- machine learning
- vertically partitioned data
- privacy issues
- privacy concerns
- horizontally partitioned data
- personal data
- privacy preservation
- data transformation
- privacy preserving data mining
- differentially private
- data publishing
- privacy guarantees
- data sets
- data analysis
- differential privacy
- data science
- data sources
- statistical learning
- horizontally partitioned
- data quality
- active learning
- privacy protection
- user privacy
- database
- learning algorithm
- knowledge discovery
- original data
- big data
- distributed data
- record linkage
- dimensionality reduction
- database management systems
- semi supervised learning
- data perturbation
- feature selection
- data anonymization
- scalar product