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We derive the optimal $(0, \delta)$-differentially private query-output independent noise-adding mechanism for single real-valued query function under a general cost-minimization framework.
Privacy-preserving logistic regression
Kamalika Chaudhuri and Claire Monteleoni · 2008
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Differential Privacy: A Survey of Results
Cynthia Dwork · 2008
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Universally utility-maximizing privacy mechanisms
Arpita Ghosh, Tim Roughgarden, and Mukund Sundararajan · 2009
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Universally optimal privacy mechanisms for minimax agents
Mangesh Gupte and Mukund Sundararajan · 2010
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Differentially private empirical risk minimization
Kamalika Chaudhuri, Claire Monteleoni, and Anand D. Sarwate · 2011
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Near-optimal differentially private principal components
Kamalika Chaudhuri, Anand Sarwate, and Kaushik Sinha · 2012
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Privacy aware learning
John Duchi, Michael Jordan, and Martin Wainwright · 2012
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Differentially private online learning
Prateek Jain, Pravesh Kothari, and Abhradeep Thakurta · 2012
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Optimal data-independent noise for differential privacy
Jordi Soria-Comas and Josep Domingo-Ferrer · 2013
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The algorithmic foundations of differential privacy
Cynthia Dwork and Aaron Roth · 2014
Cited alongside, same era.
The optimal mechanism in differential privacy
Quan Geng and Pramod Viswanath · 2014
Cited alongside, same era.
The staircase mechanism in differential privacy
Quan Geng, Peter Kairouz, Sewoong Oh, and Pramod Viswanath · 2015
Cited alongside, same era.
Privacy-preserving deep learning
Reza Shokri and Vitaly Shmatikov · 2015
Cited alongside, same era.
Deep learning with differential privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang · 2016
Cited alongside, same era.
DP-EM: Differentially Private Expectation Maximization
Mijung Park, James Foulds, Kamalika Chaudhuri, and Max Welling · 2017
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cpSGD: Communication-efficient and differentially-private distributed SGD
Naman Agarwal, Ananda Theertha Suresh, Felix Yu, Sanjiv Kumar, and Brendan McMahan · 2018
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Improving the Gaussian mechanism for differential privacy: Analytical calibration and optimal denoising
Borja Balle and Yu-Xiang Wang · 2018
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Minimax-optimal privacy-preserving sparse pca in distributed systems
Jason Ge, Zhaoran Wang, Mengdi Wang, and Han Liu · 2018
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Truncated Laplacian Mechanism for Approximate Differential Privacy
Quan Geng, Wei Ding, Ruiqi Guo, and Sanjiv Kumar · 2018
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Differentially private matrix completion revisited
Prateek Jain, Om Dipakbhai Thakkar, and Abhradeep Thakurta · 2018
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Differential privacy preservation for deep auto-encoders: an application of human behavior prediction
Ngoc-Son Phan, Yue Wang, Xintao Wu, and Dejing Dou · 2016
Cited alongside, same era.
Rényi differential privacy
Ilya Mironov · 2017
Cited alongside, same era.
Our data, ourselves: privacy via distributed noise generation
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov, and Moni Naor
Cited in the paper.
Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith
Cited in the paper.
Optimal noise adding mechanisms for approximate differential privacy
Quan Geng and Pramod Viswanath
Cited in the paper.
The optimal noise-adding mechanism in differential privacy
Quan Geng and Pramod Viswanath
Cited in the paper.
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Locally private hypothesis testing
Or Sheffet · 2018
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