Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy
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Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints

15 June 2022

Justin Whitehouse

Zhiwei Steven Wu

Papers citing "Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints"

17 / 17 papers shown

Title
Fully Adaptive Composition in Differential Privacy Justin Whitehouse Aaditya Ramdas Ryan M. Rogers Zhiwei Steven Wu 35 41 0 10 Mar 2022
The Skellam Mechanism for Differentially Private Federated Learning Naman Agarwal Peter Kairouz Ziyu Liu FedML 65 124 0 11 Oct 2021
Individual Privacy Accounting via a Renyi Filter Vitaly Feldman Tijana Zrnic 86 90 0 25 Aug 2020
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals E. Kaufmann Wouter M. Koolen 71 121 0 28 Nov 2018
Time-uniform, nonparametric, nonasymptotic confidence sequences Steven R. Howard Aaditya Ramdas Jon D. McAuliffe Jasjeet Sekhon 51 246 0 18 Oct 2018
Subsampled Rényi Differential Privacy and Analytical Moments Accountant Yu Wang Borja Balle S. Kasiviswanathan 71 398 0 31 Jul 2018
Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising Borja Balle Yu Wang MLT 66 403 0 16 May 2018
Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM Katrina Ligett Seth Neel Aaron Roth Bo Waggoner Zhiwei Steven Wu 48 94 0 30 May 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 191 6,109 0 01 Jul 2016
Privacy Odometers and Filters: Pay-as-you-Go Composition Ryan M. Rogers Aaron Roth Jonathan R. Ullman Salil P. Vadhan 48 109 0 26 May 2016
Understanding the Sparse Vector Technique for Differential Privacy Min Lyu D. Su Ninghui Li 37 166 0 05 Mar 2016
Differentially Private Ordinary Least Squares Or Sheffet 39 116 0 09 Jul 2015
Gradual Release of Sensitive Data under Differential Privacy Fragkiskos Koufogiannis Shuo Han George J. Pappas 85 36 0 02 Apr 2015
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 92 1,987 0 25 Jul 2014
The Composition Theorem for Differential Privacy Peter Kairouz Sewoong Oh Pramod Viswanath 107 680 0 04 Nov 2013
Differentially Private Empirical Risk Minimization Kamalika Chaudhuri C. Monteleoni Anand D. Sarwate 121 1,487 0 01 Dec 2009
On the `Semantics' of Differential Privacy: A Bayesian Formulation S. Kasiviswanathan Adam D. Smith 89 167 0 27 Mar 2008