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Principled Evaluation of Differentially Private Algorithms using DPBench

Principled Evaluation of Differentially Private Algorithms using DPBench

15 December 2015
Michael Hay
Ashwin Machanavajjhala
G. Miklau
Yan Chen
Dan Zhang
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Papers citing "Principled Evaluation of Differentially Private Algorithms using DPBench"

4 / 4 papers shown
Title
The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data
The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data
Georgi Ganev
Meenatchi Sundaram Muthu Selva Annamalai
Sofiane Mahiou
Emiliano De Cristofaro
50
2
0
09 Apr 2025
Low Rank Mechanism for Optimizing Batch Queries under Differential
  Privacy
Low Rank Mechanism for Optimizing Batch Queries under Differential Privacy
Ganzhao Yuan
Zhenjie Zhang
Marianne Winslett
Xiaokui Xiao
Yifan Yang
Zhifeng Hao
73
82
0
11 Dec 2012
Differentially Private Grids for Geospatial Data
Differentially Private Grids for Geospatial Data
Wahbeh H. Qardaji
Weining Yang
Ninghui Li
67
260
0
06 Sep 2012
Boosting the Accuracy of Differentially-Private Histograms Through
  Consistency
Boosting the Accuracy of Differentially-Private Histograms Through Consistency
Michael Hay
Vibhor Rastogi
G. Miklau
Dan Suciu
FedML
80
232
0
06 Apr 2009
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