<italic>p</italic>-Power Exponential Mechanisms for Differentially Private Machine Learning
Differentially private stochastic gradient descent (DP-SGD) that perturbs the clipped gradients is a popular approach for private machine learning. Gaussian mechanism GM, combined with the moments accountant (MA), has demonstrated a much better privacy-utility tradeoff than using the advanced compos...
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| Auteurs principaux: | , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
IEEE
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/d91648a81c8e4395a2b8d3247e9c873c |
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