Results 31 to 40 of about 13,061 (285)
Representing Sparse Vectors with Differential Privacy, Low Error, Optimal Space, and Fast Access
The Journal of Privacy and Confidentiality, 2022 Representing a sparse histogram, or more generally a sparse vector, is a fundamental task in differential privacy. An ideal solution would use space close to information-theoretical lower bounds, have an error distribution that depends optimally on ...
Christian Janos Lebeda +2 more
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工程科学学报, 2016 A dual-porosity medium with micro-fractured spherical matrix blocks was achieved on the basis of the structure characteristics of nano-micro pores and micro-fractures in shale gas reservoirs.
QI Qian, ZHU Wei-yao, DENG Jia, MA Qian
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The Podium Mechanism: Improving on the Laplace and Staircase Mechanisms
CoRR, 2019 The Podium mechanism guarantees ($ε, 0$)-differential privacy by sampling noise from a \emph{finite} mixture of three uniform distributions. By carefully constructing such a mixture distribution, we trivially guarantee privacy properties, while minimizing the variance of the noise added to our continuous outcome.
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Laplace's Method for Gaussian Integrals with an Application to Statistical Mechanics
The Annals of Probability, 1982 For a new class of Gaussian function space integrals depending upon $n \in \{1, 2,\cdots\}$, the exponential rate of growth or decay as $n \rightarrow \infty$ is determined. The result is applied to the calculation of the specific free energy in a model in statistical mechanics. The physical discussion is self-contained. The paper ends by proving upper
Ellis, RS, ROSEN, JS
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An Enhanced Differential Privacy Data Release Algorithm [PDF]
Jisuanji gongcheng, 2017 In order to improve the classification accuracy of released data under the same privacy preserving strength,on the basis of DiffGen algorithm,an enhanced differential privacy data release algorithm named as GiniDiff is proposed.This algorithm completely ...
SUN Kui,ZHANG Zhiyong,ZHAO Changwei
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Calibrating the Attack to Sensitivity in Differentially Private Mechanisms
Journal of Cybersecurity and Privacy, 2022 This work studies the power of adversarial attacks against machine learning algorithms that use differentially private mechanisms as their weapon.
Ayşe Ünsal, Melek Önen
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Illustrating dynamical symmetries in classical mechanics: The Laplace–Runge–Lenz vector revisited [PDF]
American Journal of Physics, 2003 The inverse square force law admits a conserved vector that lies in the plane of motion. This vector has been associated with the names of Laplace, Runge, and Lenz, among others. Many workers have explored aspects of the symmetry and degeneracy associated with this vector and with analogous dynamical symmetries. We define a conserved dynamical variable
O'Connell, Ross C., Jagannathan, Kannan
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Random Forest Algorithm for Differential Privacy Protection [PDF]
Jisuanji gongcheng, 2020 Privacy protection in data mining is one of the research hotspots in the field of information security.To address the classification problem under privacy protection requirements,this paper proposes a random forest algorithm RFDPP-Gini for differential ...
LI Yuanhang, CHEN Xianlai, LIU Li, AN Ying, LI Zhongmin
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Multiple Imputation for Parametric Inference Under a Differentially Private Laplace Mechanism
, 2019 In this paper we consider the scenario where continuous microdata have been noise infused using a differentially private Laplace mechanism for the purpose of statistical disclosure control.
Sinha, Bimal, Klein, Martin
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Optimizing Query Times for Multiple Users Scenario of Differential Privacy
IEEE Access, 2019 Differential privacy is the state-of-the-art for preserving privacy and differential privacy mechanism based on Laplace distribution with mean 0 is common practice.
Wen Huang +3 more
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