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1905.12264
Cited By
Privacy Amplification by Mixing and Diffusion Mechanisms
29 May 2019
Borja Balle
Gilles Barthe
Marco Gaboardi
J. Geumlek
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Papers citing
"Privacy Amplification by Mixing and Diffusion Mechanisms"
13 / 13 papers shown
Title
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios
Sangyeon Yoon
Wonje Jeung
Albert No
90
0
0
02 Dec 2024
Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions
T.-H. Hubert Chan
Hao Xie
Mengshi Zhao
37
1
0
14 Dec 2023
Differentially Private Gradient Flow based on the Sliced Wasserstein Distance
Ilana Sebag
Muni Sreenivas Pydi
Jean-Yves Franceschi
Alain Rakotomamonjy
Mike Gartrell
Jamal Atif
Alexandre Allauzen
24
2
0
13 Dec 2023
Privacy Loss of Noisy Stochastic Gradient Descent Might Converge Even for Non-Convex Losses
S. Asoodeh
Mario Díaz
20
6
0
17 May 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions
Lijie Hu
Ivan Habernal
Lei Shen
Di Wang
AAML
35
18
0
22 Jan 2023
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling
Jason M. Altschuler
Kunal Talwar
38
24
0
16 Oct 2022
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence)
Jiayuan Ye
Reza Shokri
FedML
35
44
0
10 Mar 2022
Differential Privacy Amplification in Quantum and Quantum-inspired Algorithms
Armando Angrisani
Mina Doosti
E. Kashefi
24
12
0
07 Mar 2022
Tailoring Gradient Methods for Differentially-Private Distributed Optimization
Yongqiang Wang
A. Nedić
27
67
0
02 Feb 2022
Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning
Carlo Alfano
Patrick Rebeschini
40
5
0
23 Sep 2021
Model Explanations with Differential Privacy
Neel Patel
Reza Shokri
Yair Zick
SILM
FedML
28
32
0
16 Jun 2020
A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via
f
f
f
-Divergences
S. Asoodeh
Jiachun Liao
Flavio du Pin Calmon
O. Kosut
Lalitha Sankar
FedML
22
38
0
16 Jan 2020
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity
Ulfar Erlingsson
Vitaly Feldman
Ilya Mironov
A. Raghunathan
Kunal Talwar
Abhradeep Thakurta
150
420
0
29 Nov 2018
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