Bayesian Pseudo Posterior Mechanism for Differentially Private Machine Learning

27 March 2025

Papers citing "Bayesian Pseudo Posterior Mechanism for Differentially Private Machine Learning"

9 / 9 papers shown

Title
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 150 180 0 01 Mar 2023
Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy Tom Farrand Fatemehsadat Mireshghallah Sahib Singh Andrew Trask FedML 53 93 0 10 Sep 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 109 655 0 20 Feb 2020
Rényi Differential Privacy of the Sampled Gaussian Mechanism Ilya Mironov Kunal Talwar Li Zhang 88 287 0 28 Aug 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 677 24,541 0 26 Jul 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 149 480 0 28 May 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J. Maddox T. Garipov Pavel Izmailov Dmitry Vetrov A. Wilson BDL UQCV 93 808 0 07 Feb 2019
Stochastic Gradient Descent as Approximate Bayesian Inference Stephan Mandt Matthew D. Hoffman David M. Blei BDL 57 599 0 13 Apr 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,155 0 01 Jul 2016