Differentially Private Variational Inference for Non-conjugate Models

27 October 2016

Papers citing "Differentially Private Variational Inference for Non-conjugate Models"

33 / 33 papers shown

Title
Noise-Aware Differentially Private Variational Inference Talal Alrawajfeh Joonas Jälkö Antti Honkela 35 0 0 25 Oct 2024
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets Ossi Raisa Antti Honkela 75 0 0 06 Feb 2024
Collaborative Learning From Distributed Data With Differentially Private Synthetic Twin Data Lukas Prediger Joonas Jälkö Antti Honkela Samuel Kaski FedML 30 1 0 09 Aug 2023
Differentially Private Statistical Inference through $β$ -Divergence One Posterior Sampling Jack Jewson Sahra Ghalebikesabi Chris Holmes 32 2 0 11 Jul 2023
On Consistent Bayesian Inference from Synthetic Data Ossi Raisa Joonas Jälkö Antti Honkela SyDa 29 2 0 26 May 2023
Differentially Private Normalizing Flows for Density Estimation, Data Synthesis, and Variational Inference with Application to Electronic Health Records Bingyue Su Yu Wang Daniele E. Schiavazzi Fang Liu 16 2 0 11 Feb 2023
Federated Variational Inference Methods for Structured Latent Variable Models Conor Hassan Roberto Salomone Kerrie Mengersen BDL FedML 21 4 0 07 Feb 2023
DPVIm: Differentially Private Variational Inference Improved Joonas Jälkö Lukas Prediger Antti Honkela Samuel Kaski 31 3 0 28 Oct 2022
Differentially private partitioned variational inference Mikko A. Heikkilä Matthew Ashman S. Swaroop Richard E. Turner Antti Honkela FedML 24 2 0 23 Sep 2022
Noise-Aware Statistical Inference with Differentially Private Synthetic Data Ossi Raisa Joonas Jälkö Samuel Kaski Antti Honkela SyDa 37 10 0 28 May 2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning Matthew Ashman T. Bui Cuong V Nguyen Efstratios Markou Adrian Weller S. Swaroop Richard E. Turner FedML 19 12 0 24 Feb 2022
Differentially private stochastic expectation propagation (DP-SEP) Margarita Vinaroz Mijung Park 25 1 0 25 Nov 2021
Locally Differentially Private Bayesian Inference Tejas D. Kulkarni Joonas Jälkö Samuel Kaski Antti Honkela 42 2 0 27 Oct 2021
Survey: Leakage and Privacy at Inference Time Marija Jegorova Chaitanya Kaul Charlie Mayor Alison Q. OÑeil Alexander Weir Roderick Murray-Smith Sotirios A. Tsaftaris PILM MIACV 19 71 0 04 Jul 2021
Gaussian Processes with Differential Privacy Antti Honkela Laila Melkas 21 2 0 01 Jun 2021
D3p -- A Python Package for Differentially-Private Probabilistic Programming Lukas Prediger Niki Loppi Samuel Kaski Antti Honkela 17 6 0 22 Mar 2021
Generating private data with user customization Xiao Chen Thomas Navidi Ram Rajagopal 11 2 0 02 Dec 2020
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
Privacy-preserving Data Sharing on Vertically Partitioned Data Razane Tajeddine Joonas Jälkö Samuel Kaski Antti Honkela FedML 36 8 0 19 Oct 2020
Controlling Privacy Loss in Sampling Schemes: an Analysis of Stratified and Cluster Sampling Mark Bun Jörg Drechsler Marco Gaboardi Audra McMillan Jayshree Sarathy 37 7 0 24 Jul 2020
Privacy-preserving data sharing via probabilistic modelling Joonas Jälkö Eemil Lagerspetz J. Haukka Sasu Tarkoma Antti Honkela Samuel Kaski 23 15 0 10 Dec 2019
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 30 30 0 27 Nov 2019
Differentially Private Federated Variational Inference Mrinank Sharma M. Hutchinson S. Swaroop Antti Honkela Richard E. Turner FedML 11 7 0 24 Nov 2019
Differentially Private Bayesian Linear Regression G. Bernstein Daniel Sheldon 32 58 0 29 Oct 2019
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models Amrita Roy Chowdhury Theodoros Rekatsinas S. Jha 10 10 0 30 May 2019
Differentially Private Markov Chain Monte Carlo Mikko A. Heikkilä Joonas Jälkö O. Dikmen Antti Honkela 27 25 0 29 Jan 2019
Bayesian Differential Privacy for Machine Learning Aleksei Triastcyn Boi Faltings 20 2 0 28 Jan 2019
Learning Rate Adaptation for Federated and Differentially Private Learning A. Koskela Antti Honkela FedML 12 27 0 11 Sep 2018
Privacy Amplification by Subsampling: Tight Analyses via Couplings and Divergences Borja Balle Gilles Barthe Marco Gaboardi 19 378 0 04 Jul 2018
On Connecting Stochastic Gradient MCMC and Differential Privacy Bai Li Changyou Chen Hao Liu Lawrence Carin 41 38 0 25 Dec 2017
Differentially Private Variational Dropout B. Ermiş A. Cemgil 21 5 0 30 Nov 2017
Differentially Private Bayesian Learning on Distributed Data Mikko A. Heikkilä Eemil Lagerspetz Samuel Kaski Kana Shimizu Sasu Tarkoma Antti Honkela FedML 25 58 0 03 Mar 2017
Variational Bayes In Private Settings (VIPS) Mijung Park James R. Foulds Kamalika Chaudhuri Max Welling 21 42 0 01 Nov 2016