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Focus on more meaningful benchmarks fe privacy
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Classroom Contents
Premonitions of Public Data for Private ML
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- 1 Intro
- 2 Private Machine Learning
- 3 Stochastic Gradient Descent (SGD)
- 4 Differentially Private Stochastic Gradient Descent (DPSGD)
- 5 MNIST
- 6 The story so far
- 7 Enter "pre-training"
- 8 Pre-training for privacy
- 9 Why is (public) pre-training useful?
- 10 Does public pre-training help? (CIFAR-10)
- 11 Does public pre-training help? ImageNet
- 12 Zero-Shot Learning for ImageNet
- 13 JFT what?
- 14 Zero-Shot Learning is taking over
- 15 Is this really "private"?
- 16 Your secrets
- 17 Personal Information
- 18 Secrets about you
- 19 How can private ML stay relevant?
- 20 Focus on more meaningful benchmarks fe privacy
- 21 Closing
