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Found 3 papers, 1 papers with code
PLAN: Variance-Aware Private Mean Estimation
Under a concentration assumption on $\mathcal{D}$, we show how to exploit skew in the vector $\boldsymbol{\sigma}$, obtaining a (zero-concentrated) differentially private mean estimate with $\ell_2$ error proportional to $\|\boldsymbol{\sigma}\|_1$.
Efficient Error Prediction for Differentially Private Algorithms
To fill the gap in the literature, we propose a novel application of factor experiments to create data aware error predictions.
Cryptography and Security
Randori: Local Differential Privacy for All
Motivated by the lack of tools to gather poll data under differential privacy, we set out to engineer our own tool.
Cryptography and Security
