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1905.12264
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Privacy Amplification by Mixing and Diffusion Mechanisms
Neural Information Processing Systems (NeurIPS), 2019
29 May 2019
Borja Balle
Gilles Barthe
Marco Gaboardi
J. Geumlek
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Papers citing
"Privacy Amplification by Mixing and Diffusion Mechanisms"
29 / 29 papers shown
Title
Certified Unlearning for Neural Networks
Anastasia Koloskova
Youssef Allouah
Animesh Jha
R. Guerraoui
Sanmi Koyejo
MU
214
8
0
08 Jun 2025
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios
Sangyeon Yoon
Wonje Jeung
Albert No
337
1
0
02 Dec 2024
Hidden State Differential Private Mini-Batch Block Coordinate Descent for Multi-convexity Optimization
Ding Chen
Chen Liu
FedML
187
0
0
11 Jul 2024
Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model
International Conference on Learning Representations (ICLR), 2024
Tudor Cebere
A. Bellet
Nicolas Papernot
403
16
0
23 May 2024
Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions
AAAI Conference on Artificial Intelligence (AAAI), 2023
T.-H. Hubert Chan
Hao Xie
Mengshi Zhao
212
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
419
3
0
13 Dec 2023
Privacy Loss of Noisy Stochastic Gradient Descent Might Converge Even for Non-Convex Losses
S. Asoodeh
Mario Díaz
158
10
0
17 May 2023
Faster high-accuracy log-concave sampling via algorithmic warm starts
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2023
Jason M. Altschuler
Sinho Chewi
315
44
0
20 Feb 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions
Findings (Findings), 2023
Lijie Hu
Ivan Habernal
Lei Shen
Haiyan Zhao
AAML
188
23
0
22 Jan 2023
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling
Annual Conference Computational Learning Theory (COLT), 2022
Jason M. Altschuler
Kunal Talwar
289
26
0
16 Oct 2022
Differentially Private Learning Needs Hidden State (Or Much Faster Convergence)
Neural Information Processing Systems (NeurIPS), 2022
Jiayuan Ye
Reza Shokri
FedML
214
56
0
10 Mar 2022
Differential Privacy Amplification in Quantum and Quantum-inspired Algorithms
Armando Angrisani
Mina Doosti
E. Kashefi
230
14
0
07 Mar 2022
Tailoring Gradient Methods for Differentially-Private Distributed Optimization
IEEE Transactions on Automatic Control (TAC), 2022
Yongqiang Wang
A. Nedić
554
93
0
02 Feb 2022
Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning
Carlo Alfano
Patrick Rebeschini
143
5
0
23 Sep 2021
Privacy Amplification via Iteration for Shuffled and Online PNSGD
Matteo Sordello
Zhiqi Bu
Jinshuo Dong
FedML
101
8
0
20 Jun 2021
Privacy Amplification Via Bernoulli Sampling
Jacob Imola
Kamalika Chaudhuri
FedML
159
8
0
21 May 2021
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent
Neural Information Processing Systems (NeurIPS), 2021
R. Chourasia
Jiayuan Ye
Reza Shokri
FedML
260
82
0
11 Feb 2021
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels
Journal of machine learning research (JMLR), 2021
Hao Wang
Rui Gao
Flavio du Pin Calmon
254
20
0
05 Feb 2021
Local Differential Privacy Is Equivalent to Contraction of
E
γ
E_γ
E
γ
-Divergence
International Symposium on Information Theory (ISIT), 2021
S. Asoodeh
Maryam Aliakbarpour
Flavio du Pin Calmon
101
32
0
02 Feb 2021
Contraction of
E
γ
E_γ
E
γ
-Divergence and Its Applications to Privacy
S. Asoodeh
Mario Díaz
Flavio du Pin Calmon
242
0
0
20 Dec 2020
Improving Utility of Differentially Private Mechanisms through Cryptography-based Technologies: a Survey
Wen Huang
Shijie Zhou
Tianqing Zhu
Yongjian Liao
FedML
217
1
0
02 Nov 2020
Three Variants of Differential Privacy: Lossless Conversion and Applications
S. Asoodeh
Jiachun Liao
Flavio du Pin Calmon
O. Kosut
Lalitha Sankar
193
45
0
14 Aug 2020
Local Differential Privacy and Its Applications: A Comprehensive Survey
Mengmeng Yang
Lingjuan Lyu
Jun Zhao
Tianqing Zhu
Kwok-Yan Lam
195
177
0
09 Aug 2020
Model Explanations with Differential Privacy
Neel Patel
Reza Shokri
Yair Zick
SILM
FedML
235
39
0
16 Jun 2020
Successive Refinement of Privacy
Antonious M. Girgis
Deepesh Data
Kamalika Chaudhuri
Christina Fragouli
Suhas Diggavi
106
3
0
24 May 2020
Privacy Amplification of Iterative Algorithms via Contraction Coefficients
International Symposium on Information Theory (ISIT), 2020
S. Asoodeh
Mario Díaz
Flavio du Pin Calmon
FedML
138
17
0
17 Jan 2020
A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via
f
f
f
-Divergences
International Symposium on Information Theory (ISIT), 2020
S. Asoodeh
Jiachun Liao
Flavio du Pin Calmon
O. Kosut
Lalitha Sankar
FedML
155
41
0
16 Jan 2020
Obfuscation via Information Density Estimation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Hsiang Hsu
S. Asoodeh
Flavio du Pin Calmon
130
12
0
17 Oct 2019
Differential privacy with partial knowledge
Damien Desfontaines
Esfandiar Mohammadi
Elisabeth Krahmer
David Basin
515
10
0
02 May 2019
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