ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2206.04572
  4. Cited By
Log-Concave and Multivariate Canonical Noise Distributions for
  Differential Privacy

Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy

9 June 2022
Jordan Awan
Jinshuo Dong
ArXivPDFHTML

Papers citing "Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy"

10 / 10 papers shown
Title
Canonical Noise Distributions and Private Hypothesis Tests
Canonical Noise Distributions and Private Hypothesis Tests
Jordan Awan
Salil P. Vadhan
13
10
0
09 Aug 2021
Optimal Accounting of Differential Privacy via Characteristic Function
Optimal Accounting of Differential Privacy via Characteristic Function
Yuqing Zhu
Jinshuo Dong
Yu Wang
33
100
0
16 Jun 2021
A Central Limit Theorem for Differentially Private Query Answering
A Central Limit Theorem for Differentially Private Query Answering
Jinshuo Dong
Weijie J. Su
Linjun Zhang
52
15
0
15 Mar 2021
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
16
34
0
30 Jan 2019
Privacy Amplification by Subsampling: Tight Analyses via Couplings and
  Divergences
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences
Borja Balle
Gilles Barthe
Marco Gaboardi
64
384
0
04 Jul 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
Deep Learning with Differential Privacy
Deep Learning with Differential Privacy
Martín Abadi
Andy Chu
Ian Goodfellow
H. B. McMahan
Ilya Mironov
Kunal Talwar
Li Zhang
FedML
SyDa
170
6,069
0
01 Jul 2016
Between Pure and Approximate Differential Privacy
Between Pure and Approximate Differential Privacy
Thomas Steinke
Jonathan R. Ullman
FedML
55
159
0
24 Jan 2015
Differentially Private Empirical Risk Minimization
Differentially Private Empirical Risk Minimization
Kamalika Chaudhuri
C. Monteleoni
Anand D. Sarwate
93
1,482
0
01 Dec 2009
On the Geometry of Differential Privacy
On the Geometry of Differential Privacy
Moritz Hardt
Kunal Talwar
92
462
0
21 Jul 2009
1