Search Results for author: Cecilia Ferrando

Found 3 papers, 1 papers with code

Private Regression via Data-Dependent Sufficient Statistic Perturbation

1 code implementation23 May 2024 Cecilia Ferrando, Daniel Sheldon

We extend this result to logistic regression by developing an approximate objective that can be expressed in terms of sufficient statistics, resulting in a novel and highly competitive SSP approach for logistic regression.

regression

Combining Public and Private Data

no code implementations29 Oct 2021 Cecilia Ferrando, Jennifer Gillenwater, Alex Kulesza

We argue that our mechanism is preferable to techniques that preserve the privacy of individuals by subsampling data proportionally to the privacy needs of users.

Parametric Bootstrap for Differentially Private Confidence Intervals

no code implementations14 Jun 2020 Cecilia Ferrando, Shufan Wang, Daniel Sheldon

The goal of this paper is to develop a practical and general-purpose approach to construct confidence intervals for differentially private parametric estimation.

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