SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles.
Cuong TranKeyu ZhuFerdinando FiorettoPascal Van HentenryckPublished in: CoRR (2022)
Keyphrases
- professional development
- highly scalable
- web scale
- learning process
- ensemble learning
- random forests
- data aggregation
- decision trees
- lightweight
- privacy preserving
- ensemble methods
- aggregation operators
- computer assisted language learning
- database
- rank aggregation
- imbalanced data
- ensemble classifier
- feature selection