Timezone: »
Differentially Private Hamiltonian Monte Carlo
Ossi Räisä · Antti Koskela · Antti Honkela
Event URL: https://openreview.net/forum?id=oqNqsnOVwlK »
We present DP-HMC, a variant of Hamiltonian Monte Carlo (HMC) that is differentially private (DP). We use the penalty algorithm of Yildirim and Ermis to make the acceptance test private, and add Gaussian noise to the gradients of the target distribution to make the HMC proposal private. Our main contribution is showing that DP-HMC has the correct invariant distribution, and is ergodic. We also compare DP-HMC with the existing penalty algorithm, as well as DP-SGLD and DP-SGNHT.
Author Information
Ossi Räisä (University of Helsinki)
Antti Koskela (University of Helsinki)
Antti Honkela (University of Helsinki)
More from the Same Authors
-
2020 : Tight Approximate Differential Privacy for Discrete-Valued Mechanisms Using FFT »
Antti Koskela -
2021 : Tight Accounting in the Shuffle Model of Differential Privacy »
Antti Koskela · Mikko Heikkilä · Antti Honkela -
2022 : Individual Privacy Accounting with Gaussian Differential Privacy »
Antti Koskela · Marlon Tobaben · Antti Honkela -
2023 Poster: Practical Differentially Private Hyperparameter Tuning with Subsampling »
Antti Koskela · Tejas Kulkarni -
2023 Poster: Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners »
Rachel Redberg · Antti Koskela · Yu-Xiang Wang -
2023 Competition: NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA »
Dimosthenis Karatzas · Rubèn Tito · Lei Kang · Mohamed Ali Souibgui · Khanh Nguyen · Raouf Kerkouche · Kangsoo Jung · Marlon Tobaben · Joonas Jälkö · Vincent Poulain d'Andecy · Aurélie JOSEPH · Ernest Valveny · Josep Llados · Antti Honkela · Mario Fritz -
2022 : Noise-Aware Statistical Inference with Differentially Private Synthetic Data »
Ossi Räisä · Joonas Jälkö · Antti Honkela · Samuel Kaski -
2021 Workshop: Privacy in Machine Learning (PriML) 2021 »
Yu-Xiang Wang · Borja Balle · Giovanni Cherubin · Kamalika Chaudhuri · Antti Honkela · Jonathan Lebensold · Casey Meehan · Mi Jung Park · Adrian Weller · Yuqing Zhu -
2020 Workshop: Privacy Preserving Machine Learning - PriML and PPML Joint Edition »
Borja Balle · James Bell · Aurélien Bellet · Kamalika Chaudhuri · Adria Gascon · Antti Honkela · Antti Koskela · Casey Meehan · Olga Ohrimenko · Mi Jung Park · Mariana Raykova · Mary Anne Smart · Yu-Xiang Wang · Adrian Weller -
2019 : Poster Session »
Clement Canonne · Kwang-Sung Jun · Seth Neel · Di Wang · Giuseppe Vietri · Liwei Song · Jonathan Lebensold · Huanyu Zhang · Lovedeep Gondara · Ang Li · FatemehSadat Mireshghallah · Jinshuo Dong · Anand D Sarwate · Antti Koskela · Joonas Jälkö · Matt Kusner · Dingfan Chen · Mi Jung Park · Ashwin Machanavajjhala · Jayashree Kalpathy-Cramer · · Vitaly Feldman · Andrew Tomkins · Hai Phan · Hossein Esfandiari · Mimansa Jaiswal · Mrinank Sharma · Jeff Druce · Casey Meehan · Zhengli Zhao · Hsiang Hsu · Davis Railsback · Abraham Flaxman · · Julius Adebayo · Aleksandra Korolova · Jiaming Xu · Naoise Holohan · Samyadeep Basu · Matthew Joseph · My Thai · Xiaoqian Yang · Ellen Vitercik · Michael Hutchinson · Chenghong Wang · Gregory Yauney · Yuchao Tao · Chao Jin · Si Kai Lee · Audra McMillan · Rauf Izmailov · Jiayi Guo · Siddharth Swaroop · Tribhuvanesh Orekondy · Hadi Esmaeilzadeh · Kevin Procopio · Alkis Polyzotis · Jafar Mohammadi · Nitin Agrawal -
2019 Workshop: Privacy in Machine Learning (PriML) »
Borja Balle · Kamalika Chaudhuri · Antti Honkela · Antti Koskela · Casey Meehan · Mi Jung Park · Mary Anne Smart · Mary Anne Smart · Adrian Weller -
2019 Poster: Differentially Private Markov Chain Monte Carlo »
Mikko Heikkilä · Joonas Jälkö · Onur Dikmen · Antti Honkela -
2019 Spotlight: Differentially Private Markov Chain Monte Carlo »
Mikko Heikkilä · Joonas Jälkö · Onur Dikmen · Antti Honkela -
2018 : Poster Session »
Phillipp Schoppmann · Patrick Yu · Valerie Chen · Travis Dick · Marc Joye · Ningshan Zhang · Frederik Harder · Olli Saarikivi · Théo Ryffel · Yunhui Long · Théo JOURDAN · Di Wang · Antonio Marcedone · Negev Shekel Nosatzki · Yatharth A Dubey · Antti Koskela · Peter Bloem · Aleksandra Korolova · Martin Bertran · Hao Chen · Galen Andrew · Natalia Martinez · Janardhan Kulkarni · Jonathan Passerat-Palmbach · Guillermo Sapiro · Amrita Roy Chowdhury -
2018 Workshop: Machine Learning Open Source Software 2018: Sustainable communities »
Heiko Strathmann · Viktor Gal · Ryan Curtin · Antti Honkela · Sergey Lisitsyn · Cheng Soon Ong -
2017 : Invited talk: Differential privacy and Bayesian learning »
Antti Honkela -
2017 Poster: Differentially private Bayesian learning on distributed data »
Mikko Heikkilä · Eemil Lagerspetz · Samuel Kaski · Kana Shimizu · Sasu Tarkoma · Antti Honkela -
2015 : Genome-wide modelling of transcription kinetics reveals patterns of RNA production delays »
Antti Honkela -
2013 Workshop: Machine Learning Open Source Software: Towards Open Workflows »
Antti Honkela · Cheng Soon Ong