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Privacy-preserving ML @ FCAI
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Classroom Contents
Noise-Aware Statistical Inference with Differentially Private Synthetic Data
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- 1 Intro
- 2 Privacy-preserving ML @ FCAI
- 3 Introduction: Synthetic Data
- 4 Introduction: Differential Privacy
- 5 Introduction: Analysing Synthetic Data
- 6 Background: Differential Privacy
- 7 The Solution: Noise-Aware Multiple Imputation (NA+MI)
- 8 Rubin's Rules
- 9 The Bayesian Model - Variables
- 10 Results - Toy Example
- 11 Results - UCI Adult Dataset
- 12 Results - Marginal Accuracy on Adult
- 13 Limitations
- 14 Conclusion
