Differentially Private Synthetic Data Generation via Foundation Model APIs

Differentially Private Synthetic Data Generation via Foundation Model APIs

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Conclusions

15 of 15

15 of 15

Conclusions

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Classroom Contents

Differentially Private Synthetic Data Generation via Foundation Model APIs

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  1. 1 Intro
  2. 2 (Generative) Neural networks can memorize!
  3. 3 Differential Privacy (DP)
  4. 4 Existing Approaches
  5. 5 DP Synthetic Data via APIs
  6. 6 Why can it work?
  7. 7 Diffusion Models
  8. 8 Distance function
  9. 9 Downstream Classification
  10. 10 Private Evolution at work
  11. 11 Stable Diffusion
  12. 12 Non-private convergence of PE
  13. 13 Proof Sketch
  14. 14 Intrinsic dimension
  15. 15 Conclusions

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