A BLMAB-based parameter tuning approach for privacy-preserving prediction markets.
Takumi SatoNaoki FukutaPublished in: ICA (2017)
Keyphrases
- parameter tuning
- privacy preserving
- prediction markets
- mechanism design
- privacy preserving data mining
- kernel methods
- privacy preservation
- cooperative game theory
- vertically partitioned data
- sensitive information
- market prices
- private information
- parameter settings
- privacy concerns
- privacy issues
- multi party
- privacy protection
- privacy sensitive
- horizontally partitioned data
- privacy preserving association rule mining
- data perturbation
- data privacy
- preserving privacy
- privacy requirements
- game theory
- private data
- differential privacy
- homomorphic encryption
- scalar product
- partitioned data
- sensitive data
- genetic algorithm