Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo

26 February 2015

Papers citing "Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo"

45 / 45 papers shown

Title
Distributed Differentially Private Data Analytics via Secure Sketching Jakob Burkhardt Hannah Keller Claudio Orlandi Chris Schwiegelshohn FedML 82 0 0 30 Nov 2024
Noise-Aware Differentially Private Variational Inference Talal Alrawajfeh Joonas Jälkö Antti Honkela 32 0 0 25 Oct 2024
Delving into Differentially Private Transformer Youlong Ding Xueyang Wu Yining Meng Yonggang Luo Hao Wang Weike Pan 29 5 0 28 May 2024
The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank Amitay Bar Rotem Mulayoff T. Michaeli Ronen Talmon 56 0 0 21 Feb 2024
An In-Depth Examination of Requirements for Disclosure Risk Assessment Ron S. Jarmin John M. Abowd Robert Ashmead Ryan Cumings-Menon N. Goldschlag ... Jerome P. Reiter Rolando A. Rodríguez Ian M. Schmutte V. Velkoff Pavel I Zhuravlev 24 9 0 13 Oct 2023
DPpack: An R Package for Differentially Private Statistical Analysis and Machine Learning S. Giddens F. Liu 25 1 0 19 Sep 2023
Differential Privacy for Class-based Data: A Practical Gaussian Mechanism Raksha Ramakrishna Anna Scaglione Tong Wu Nikhil Ravi S. Peisert 22 4 0 08 Jun 2023
Differentially Private Distributed Bayesian Linear Regression with MCMC Barics Alparslan S. Yıldırım cS. .Ilker Birbil FedML 23 1 0 31 Jan 2023
Near Optimal Private and Robust Linear Regression Xiyang Liu Prateek Jain Weihao Kong Sewoong Oh A. Suggala 35 9 0 30 Jan 2023
Forget Unlearning: Towards True Data-Deletion in Machine Learning R. Chourasia Neil Shah MU 13 39 0 17 Oct 2022
An Ensemble Teacher-Student Learning Approach with Poisson Sub-sampling to Differential Privacy Preserving Speech Recognition Chao-Han Huck Yang Jun Qi Sabato Marco Siniscalchi Chin-Hui Lee 16 4 0 12 Oct 2022
Self-Supervised Pretraining for Differentially Private Learning Arash Asadian Evan Weidner Lei Jiang PICV 25 3 0 14 Jun 2022
Exact Privacy Guarantees for Markov Chain Implementations of the Exponential Mechanism with Artificial Atoms Jeremy Seeman M. Reimherr Aleksandra B. Slavkovic 19 11 0 03 Apr 2022
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics A. Banerjee Tiancong Chen Xinyan Li Yingxue Zhou 18 8 0 09 Jan 2022
On Convergence of Federated Averaging Langevin Dynamics Wei Deng Qian Zhang Yi-An Ma Zhao-quan Song Guang Lin FedML 22 16 0 09 Dec 2021
Differentially private stochastic expectation propagation (DP-SEP) Margarita Vinaroz Mijung Park 17 1 0 25 Nov 2021
Dirichlet Mechanism for Differentially Private KL Divergence Minimization Donlapark Ponnoprat 10 0 0 03 Oct 2021
Perturbed M-Estimation: A Further Investigation of Robust Statistics for Differential Privacy Aleksandra B. Slavkovic Roberto Molinari 17 5 0 05 Aug 2021
Privacy-Aware Rejection Sampling Jordan Awan Vinayak A. Rao 24 7 0 02 Aug 2021
Differentially Private Hamiltonian Monte Carlo Ossi Raisa A. Koskela Antti Honkela 11 6 0 17 Jun 2021
Optimal Accounting of Differential Privacy via Characteristic Function Yuqing Zhu Jinshuo Dong Yu-Xiang Wang 15 98 0 16 Jun 2021
Differentially private inference via noisy optimization Marco Avella-Medina Casey Bradshaw Po-Ling Loh FedML 25 29 0 19 Mar 2021
Differentially Private Bayesian Inference for Generalized Linear Models Tejas D. Kulkarni Joonas Jälkö A. Koskela Samuel Kaski Antti Honkela 18 31 0 01 Nov 2020
Reviewing and Improving the Gaussian Mechanism for Differential Privacy Jun Zhao Teng Wang Tao Bai Kwok-Yan Lam Zhiying Xu Shuyu Shi Xuebin Ren Xinyu Yang Yang Liu Han Yu 22 30 0 27 Nov 2019
Differentially Private Bayesian Linear Regression G. Bernstein Daniel Sheldon 27 58 0 29 Oct 2019
Synthetic Data for Deep Learning Sergey I. Nikolenko 46 348 0 25 Sep 2019
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection Bingzhe Wu Shiwan Zhao Chaochao Chen Haoyang Xu Li Wang Xiaolu Zhang Guangyu Sun Jun Zhou 14 45 0 21 Aug 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 16 135 0 16 Jul 2019
On Privacy Protection of Latent Dirichlet Allocation Model Training Fangyuan Zhao Xuebin Ren Shusen Yang Xinyu Yang 20 5 0 04 Jun 2019
KNG: The K-Norm Gradient Mechanism M. Reimherr Jordan Awan 21 23 0 23 May 2019
Differentially Private Markov Chain Monte Carlo Mikko A. Heikkilä Joonas Jälkö O. Dikmen Antti Honkela 16 25 0 29 Jan 2019
Profile-Based Privacy for Locally Private Computations J. Geumlek Kamalika Chaudhuri 14 17 0 21 Jan 2019
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget Jaewoo Lee Daniel Kifer 14 156 0 28 Aug 2018
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors Gintare Karolina Dziugaite Daniel M. Roy MLT 20 144 0 26 Dec 2017
On Connecting Stochastic Gradient MCMC and Differential Privacy Bai Li Changyou Chen Hao Liu Lawrence Carin 27 38 0 25 Dec 2017
Per-instance Differential Privacy Yu-Xiang Wang 29 5 0 24 Jul 2017
Fractional Langevin Monte Carlo: Exploring Lévy Driven Stochastic Differential Equations for Markov Chain Monte Carlo Umut Simsekli 30 45 0 12 Jun 2017
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible Kai Zheng Wenlong Mou Liwei Wang 34 41 0 11 Jun 2017
Differentially Private Variational Inference for Non-conjugate Models Joonas Jälkö O. Dikmen Antti Honkela FedML 13 48 0 27 Oct 2016
On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis James R. Foulds J. Geumlek Max Welling Kamalika Chaudhuri 18 102 0 23 Mar 2016
Pufferfish Privacy Mechanisms for Correlated Data Shuang Song Yizhen Wang Kamalika Chaudhuri 17 148 0 13 Mar 2016
Stochastic Quasi-Newton Langevin Monte Carlo Umut Simsekli Roland Badeau A. Cemgil G. Richard BDL 14 59 0 10 Feb 2016
Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA Yannis Papanikolaou James R. Foulds T. Rubin Grigorios Tsoumakas 23 34 0 08 May 2015
Fast Differentially Private Matrix Factorization Ziqi Liu Yu-Xiang Wang Alex Smola FedML 40 124 0 06 May 2015
Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle Yu-Xiang Wang Jing Lei S. Fienberg 28 103 0 23 Feb 2015