Privacy and fairness cannot both be guaranteed in facility location over all datasets, but mechanisms exist that are optimal or near-optimal on welfare and fairness for natural data while preserving worst-case differential privacy.
DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accu- racy?
2 Pith papers cite this work. Polarity classification is still indexing.
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INO-SGD down-weights data in each batch to improve model performance on strongly private data while satisfying individualized differential privacy constraints.
citing papers explorer
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Tradeoffs in Privacy, Welfare, and Fairness for Facility Location
Privacy and fairness cannot both be guaranteed in facility location over all datasets, but mechanisms exist that are optimal or near-optimal on welfare and fairness for natural data while preserving worst-case differential privacy.
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INO-SGD: Addressing Utility Imbalance under Individualized Differential Privacy
INO-SGD down-weights data in each batch to improve model performance on strongly private data while satisfying individualized differential privacy constraints.