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Privately Publishable Per-instance Privacy

Privately Publishable Per-instance Privacy

3 November 2021
Rachel Redberg
Yu-Xiang Wang
ArXivPDFHTML

Papers citing "Privately Publishable Per-instance Privacy"

14 / 14 papers shown
Title
Towards Optimal Differentially Private Regret Bounds in Linear MDPs
Towards Optimal Differentially Private Regret Bounds in Linear MDPs
Sharan Sahu
55
0
0
12 Apr 2025
Privacy Amplification for the Gaussian Mechanism via Bounded Support
Privacy Amplification for the Gaussian Mechanism via Bounded Support
Shengyuan Hu
Saeed Mahloujifar
Virginia Smith
Kamalika Chaudhuri
Chuan Guo
FedML
33
1
0
07 Mar 2024
On the Privacy of Selection Mechanisms with Gaussian Noise
On the Privacy of Selection Mechanisms with Gaussian Noise
Jonathan Lebensold
Doina Precup
Borja Balle
29
0
0
09 Feb 2024
Improving the Privacy and Practicality of Objective Perturbation for
  Differentially Private Linear Learners
Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners
Rachel Redberg
Antti Koskela
Yu-Xiang Wang
68
5
0
31 Dec 2023
Privately Answering Queries on Skewed Data via Per Record Differential
  Privacy
Privately Answering Queries on Skewed Data via Per Record Differential Privacy
Jeremy Seeman
William Sexton
David Pujol
Ashwin Machanavajjhala
17
4
0
19 Oct 2023
Probing the Transition to Dataset-Level Privacy in ML Models Using an
  Output-Specific and Data-Resolved Privacy Profile
Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile
Tyler LeBlond
Joseph Munoz
Fred Lu
Maya Fuchs
Elliott Zaresky-Williams
Edward Raff
Brian Testa
14
3
0
27 Jun 2023
Bounding Training Data Reconstruction in DP-SGD
Bounding Training Data Reconstruction in DP-SGD
Jamie Hayes
Saeed Mahloujifar
Borja Balle
AAML
FedML
31
39
0
14 Feb 2023
Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with
  Differential Privacy
Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy
Rachel Redberg
Yuqing Zhu
Yu-Xiang Wang
30
7
0
31 Dec 2022
Individual Privacy Accounting with Gaussian Differential Privacy
Individual Privacy Accounting with Gaussian Differential Privacy
A. Koskela
Marlon Tobaben
Antti Honkela
32
18
0
30 Sep 2022
Individual Privacy Accounting for Differentially Private Stochastic
  Gradient Descent
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
Da Yu
Gautam Kamath
Janardhan Kulkarni
Tie-Yan Liu
Jian Yin
Huishuai Zhang
11
17
0
06 Jun 2022
Offline Reinforcement Learning with Differential Privacy
Offline Reinforcement Learning with Differential Privacy
Dan Qiao
Yu-Xiang Wang
OffRL
33
23
0
02 Jun 2022
Individual Privacy Accounting via a Renyi Filter
Individual Privacy Accounting via a Renyi Filter
Vitaly Feldman
Tijana Zrnic
51
86
0
25 Aug 2020
SoK: Differential Privacies
SoK: Differential Privacies
Damien Desfontaines
Balázs Pejó
26
121
0
04 Jun 2019
Mechanism Design in Large Games: Incentives and Privacy
Michael Kearns
Mallesh M. Pai
Aaron Roth
Jonathan R. Ullman
82
182
0
17 Jul 2012
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