Local privacy mechanisms preserve rate-double-robustness, enabling unbiased and semiparametrically efficient inference on target parameters indexed linearly by infinite-dimensional and nonlinearly by low-dimensional components from noisy private data.
and Li, Lingling and Mukherjee, Rajarshi and Tchetgen Tchetgen, Eric and
2 Pith papers cite this work. Polarity classification is still indexing.
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Develops higher-order influence function estimators for implicitly defined parameters in non-separable structural models using U-processes theory.
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Private Rate-Double-Robust Inference
Local privacy mechanisms preserve rate-double-robustness, enabling unbiased and semiparametrically efficient inference on target parameters indexed linearly by infinite-dimensional and nonlinearly by low-dimensional components from noisy private data.
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Higher-Order Debiased Estimators for General Treatment Models
Develops higher-order influence function estimators for implicitly defined parameters in non-separable structural models using U-processes theory.