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Robustness Implies Privacy in Statistical Estimation
We study the relationship between adversarial robustness and differential privacy in high-dimensional algorithmic statistics.
Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism
SoS proofs to algorithms is a key theme in numerous recent works in high-dimensional algorithmic statistics -- estimators which apparently require exponential running time but whose analysis can be captured by low-degree Sum of Squares proofs can be automatically turned into polynomial-time algorithms with the same provable guarantees.
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