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Privacy Amplification by Mixing and Diffusion Mechanisms

Neural Information Processing Systems (NeurIPS), 2019

29 May 2019

Gilles Barthe

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 222 8 0 08 Jun 2025
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios Sangyeon Yoon Wonje Jeung Albert No 357 1 0 02 Dec 2024
Hidden State Differential Private Mini-Batch Block Coordinate Descent for Multi-convexity Optimization Ding Chen Chen Liu FedML 219 0 0 11 Jul 2024
Tighter Privacy Auditing of DP-SGD in the Hidden State Threat ModelInternational Conference on Learning Representations (ICLR), 2024 Tudor Cebere A. Bellet Nicolas Papernot 415 16 0 23 May 2024
Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective FunctionsAAAI Conference on Artificial Intelligence (AAAI), 2023 T.-H. Hubert Chan Hao Xie Mengshi Zhao 224 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 162 10 0 17 May 2023
Faster high-accuracy log-concave sampling via algorithmic warm startsIEEE 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 DirectionsFindings (Findings), 2023 Lijie Hu Ivan Habernal Lei Shen Haiyan Zhao AAML 204 23 0 22 Jan 2023
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave SamplingAnnual Conference Computational Learning Theory (COLT), 2022 Jason M. Altschuler Kunal Talwar 293 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 234 56 0 10 Mar 2022
Differential Privacy Amplification in Quantum and Quantum-inspired Algorithms Armando Angrisani Mina Doosti E. Kashefi 234 15 0 07 Mar 2022
Tailoring Gradient Methods for Differentially-Private Distributed OptimizationIEEE Transactions on Automatic Control (TAC), 2022 Yongqiang Wang A. Nedić 582 95 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 DescentNeural Information Processing Systems (NeurIPS), 2021 R. Chourasia Jiayuan Ye Reza Shokri FedML 300 82 0 11 Feb 2021
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise ChannelsJournal 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 $E_γ$ -DivergenceInternational Symposium on Information Theory (ISIT), 2021 S. Asoodeh Maryam Aliakbarpour Flavio du Pin Calmon 101 32 0 02 Feb 2021
Contraction of $E_γ$ -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 205 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 195 178 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 CoefficientsInternational Symposium on Information Theory (ISIT), 2020 S. Asoodeh Mario Díaz Flavio du Pin Calmon FedML 142 17 0 17 Jan 2020
A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via $f$ -DivergencesInternational 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 EstimationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Hsiang Hsu S. Asoodeh Flavio du Pin Calmon 134 12 0 17 Oct 2019
Differential privacy with partial knowledge Damien Desfontaines Esfandiar Mohammadi Elisabeth Krahmer David Basin 531 10 0 02 May 2019