Jun 13, 2024 · Here, we introduce the \Delta-divergence between mechanisms which quantifies the worst-case excess privacy vulnerability of choosing one ...
Abstract. In differentially private (DP) machine learning, the privacy guarantees of DP mechanisms are of- ten reported and compared on the basis of a ...
Jun 13, 2024 · Protecting private information in machine learning (ML) workflows involving sensitive data is of paramount importance. Differential Privacy (DP) ...
Jul 10, 2024 · This paper presents a Bayesian analysis of the behavior of differential privacy mechanisms beyond the calibration point, where the privacy- ...
Jul 11, 2024 · Beyond the Calibration Point: Mechanism Comparison in Differential Privacy. ... In differentially private (DP) machine learning, the privacy ...
Compared to VCG mechanism. • JDP gives item prices; VCG charges payments on bundles. • JDP approximate envy-free; VCG not envy-free. Page 30. Joint Differential ...
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Jun 13, 2024 · Beyond the Calibration Point: Mechanism Comparison in Differential Privacy · Georgios Kaissis · Stefan Kolek · Borja Balle · Jamie Hayes · Daniel ...
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What are the limitations of differential privacy?
Our primary mechanism is a general one that automatically converts any existing differentially private algorithm into one that satisfies. PDP. We also present a ...
Feb 1, 2023 · This paper studies the calibration of differentially private learners based on stochastic gradient descent. The paper first observes the ...
Missing: Mechanism | Show results with:Mechanism
In Section 4, we empirically evaluate our noise reduction meta-method, which applies to any ERM technique which can be described as a post-processing of the ...