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Perturbed M-Estimation: A Further Investigation of Robust Statistics for
  Differential Privacy

Perturbed M-Estimation: A Further Investigation of Robust Statistics for Differential Privacy

5 August 2021
Aleksandra B. Slavkovic
Roberto Molinari
ArXivPDFHTML

Papers citing "Perturbed M-Estimation: A Further Investigation of Robust Statistics for Differential Privacy"

13 / 13 papers shown
Title
Privacy-preserving parametric inference: a case for robust statistics
Privacy-preserving parametric inference: a case for robust statistics
Marco Avella-Medina
26
51
0
22 Nov 2019
KNG: The K-Norm Gradient Mechanism
KNG: The K-Norm Gradient Mechanism
M. Reimherr
Jordan Awan
43
23
0
23 May 2019
Benefits and Pitfalls of the Exponential Mechanism with Applications to
  Hilbert Spaces and Functional PCA
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA
Jordan Awan
Ana M. Kenney
M. Reimherr
Aleksandra B. Slavkovic
11
34
0
30 Jan 2019
The Structure of Optimal Private Tests for Simple Hypotheses
The Structure of Optimal Private Tests for Simple Hypotheses
C. Canonne
Gautam Kamath
Audra McMillan
Adam D. Smith
Jonathan R. Ullman
46
72
0
27 Nov 2018
Differentially Private Uniformly Most Powerful Tests for Binomial Data
Differentially Private Uniformly Most Powerful Tests for Binomial Data
Jordan Awan
Aleksandra B. Slavkovic
53
53
0
23 May 2018
On-Average KL-Privacy and its equivalence to Generalization for
  Max-Entropy Mechanisms
On-Average KL-Privacy and its equivalence to Generalization for Max-Entropy Mechanisms
Yu Wang
Jing Lei
S. Fienberg
34
48
0
08 May 2016
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit
  and Independence Testing
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing
Marco Gaboardi
H. Lim
Ryan M. Rogers
Salil P. Vadhan
52
139
0
07 Feb 2016
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo
Yu Wang
S. Fienberg
Alex Smola
46
248
0
26 Feb 2015
Near-Optimal Algorithms for Differentially-Private Principal Components
Near-Optimal Algorithms for Differentially-Private Principal Components
Kamalika Chaudhuri
Anand D. Sarwate
Kaushik Sinha
54
153
0
12 Jul 2012
Convergence Rates for Differentially Private Statistical Estimation
Convergence Rates for Differentially Private Statistical Estimation
Kamalika Chaudhuri
Daniel J. Hsu
FedML
48
50
0
27 Jun 2012
Differential Privacy for Functions and Functional Data
Differential Privacy for Functions and Functional Data
Rob Hall
Alessandro Rinaldo
Larry A. Wasserman
51
180
0
12 Mar 2012
Differentially Private Empirical Risk Minimization
Differentially Private Empirical Risk Minimization
Kamalika Chaudhuri
C. Monteleoni
Anand D. Sarwate
93
1,482
0
01 Dec 2009
A statistical framework for differential privacy
A statistical framework for differential privacy
Larry A. Wasserman
Shuheng Zhou
89
482
0
16 Nov 2008
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