Privacy-Preserving Object Detection & Localization Using Distributed Machine Learning: A Case Study of Infant Eyeblink Conditioning.
Stefan ZwaardHenk-Jan BoeleHani AlersChristos StrydisCasey Lew-WilliamsZaid Al-ArsPublished in: CoRR (2020)
Keyphrases
- privacy preserving
- object detection
- machine learning
- horizontally partitioned data
- horizontally partitioned
- partitioned data
- multi party
- privacy sensitive
- privacy preserving data mining
- distributed data mining
- vertically partitioned data
- secure multiparty computation
- privacy preservation
- personal data
- sensitive information
- privacy preserving classification
- distributed environment
- private information
- data mining
- record linkage
- privacy guarantees
- scalar product
- distributed systems
- data privacy
- privacy preserving association rule mining
- privacy issues
- decision trees
- sensitive data
- naive bayesian classification
- private data
- peer to peer
- knowledge discovery
- data analysis
- data perturbation
- databases
- feature selection
- support vector
- support vector machine
- communication cost
- differential privacy
- study proposes
- privacy protection
- privacy concerns