Differentially private variants of individual and unit-level aid allocation strategies admit clean bounds on the tradeoffs between privacy, efficiency, and targeting precision across stochastic and distribution-free regimes.
Private stochastic convex optimization: optimal rates in linear time
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
Differential privacy in policy optimization adds sample complexity costs that often appear as lower-order terms rather than dominating the bounds.
citing papers explorer
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Privacy, Prediction, and Allocation
Differentially private variants of individual and unit-level aid allocation strategies admit clean bounds on the tradeoffs between privacy, efficiency, and targeting precision across stochastic and distribution-free regimes.
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On the Sample Complexity of Differentially Private Policy Optimization
Differential privacy in policy optimization adds sample complexity costs that often appear as lower-order terms rather than dominating the bounds.