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Found 2 papers, 1 papers with code
Pain-Free Random Differential Privacy with Sensitivity Sampling
Popular approaches to differential privacy, such as the Laplace and exponential mechanisms, calibrate randomised smoothing through global sensitivity of the target non-private function.
On the privacy-utility trade-off in differentially private hierarchical text classification
This work investigates the privacy-utility trade-off in hierarchical text classification with differential privacy guarantees, and identifies neural network architectures that offer superior trade-offs.
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