Locally Private Bayesian Inference for Count Models

Locally Private Bayesian Inference for Count Models

22 March 2018

Zhiwei Steven Wu

Alexandra Schofield

Mingyuan Zhou

Hanna M. Wallach

Papers citing "Locally Private Bayesian Inference for Count Models"

10 / 10 papers shown

Title
Technical Insights and Legal Considerations for Advancing Federated Learning in Bioinformatics Daniele Malpetti Marco Scutari Francesco Gualdi Jessica van Setten Sander van der Laan Saskia Haitjema Aaron Mark Lee Isabelle Hering Francesca Mangili FedML AI4CE 109 1 0 12 Mar 2025
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 102 167 0 01 Mar 2023
Data Augmentation MCMC for Bayesian Inference from Privatized Data Nianqiao P. Ju Jordan Awan Ruobin Gong Vinayak A. Rao 32 23 0 01 Jun 2022
The Skellam Mechanism for Differentially Private Federated Learning Naman Agarwal Peter Kairouz Ziyu Liu FedML 22 122 0 11 Oct 2021
Differentially Private Bayesian Inference for Generalized Linear Models Tejas D. Kulkarni Joonas Jälkö A. Koskela Samuel Kaski Antti Honkela 35 31 0 01 Nov 2020
Differentially Private Bayesian Linear Regression G. Bernstein Daniel Sheldon 35 58 0 29 Oct 2019
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models Amrita Roy Chowdhury Theodoros Rekatsinas S. Jha 15 10 0 30 May 2019
Profile-Based Privacy for Locally Private Computations J. Geumlek Kamalika Chaudhuri 21 17 0 21 Jan 2019
Differentially Private Bayesian Inference for Exponential Families G. Bernstein Daniel Sheldon 33 48 0 06 Sep 2018
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm Christopher DeCarolis Mukul Ram Seyed-Alireza Esmaeili Yu-Xiang Wang Furong Huang FedML 13 12 0 25 May 2018