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. 2205.01258
  4. Cited By
Universal Optimality and Robust Utility Bounds for Metric Differential
  Privacy

Universal Optimality and Robust Utility Bounds for Metric Differential Privacy

3 May 2022
Natasha Fernandes
Annabelle McIver
C. Palamidessi
Ming Ding
ArXivPDFHTML

Papers citing "Universal Optimality and Robust Utility Bounds for Metric Differential Privacy"

8 / 8 papers shown
Title
Empirical Calibration and Metric Differential Privacy in Language Models
Empirical Calibration and Metric Differential Privacy in Language Models
Pedro Faustini
Natasha Fernandes
Annabelle McIver
Mark Dras
70
0
0
18 Mar 2025
Practical Implications of Implementing Local Differential Privacy for Smart grids
Practical Implications of Implementing Local Differential Privacy for Smart grids
Khadija Hafeez
M. H. Rehmani
Sumita Mishra
Donna O'Shea
44
0
0
14 Mar 2025
Metric geometry of the privacy-utility tradeoff
Metric geometry of the privacy-utility tradeoff
M. Boedihardjo
Thomas Strohmer
Roman Vershynin
36
1
0
01 May 2024
Near-Universally-Optimal Differentially Private Minimum Spanning Trees
Near-Universally-Optimal Differentially Private Minimum Spanning Trees
Richard Hladík
Jakub Tetek
37
2
0
23 Apr 2024
Advancing Personalized Federated Learning: Group Privacy, Fairness, and
  Beyond
Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond
Filippo Galli
Kangsoo Jung
Sayan Biswas
C. Palamidessi
Tommaso Cucinotta
FedML
36
10
0
01 Sep 2023
A novel analysis of utility in privacy pipelines, using Kronecker
  products and quantitative information flow
A novel analysis of utility in privacy pipelines, using Kronecker products and quantitative information flow
Mário S. Alvim
Natasha Fernandes
Annabelle McIver
Carroll Morgan
Gabriel H. Nunes
29
5
0
22 Aug 2023
Directional Privacy for Deep Learning
Directional Privacy for Deep Learning
Pedro Faustini
Natasha Fernandes
Shakila Mahjabin Tonni
Annabelle McIver
Mark Dras
19
1
0
09 Nov 2022
Optimal Geo-Indistinguishable Mechanisms for Location Privacy
Optimal Geo-Indistinguishable Mechanisms for Location Privacy
N. E. Bordenabe
K. Chatzikokolakis
C. Palamidessi
57
275
0
20 Feb 2014
1