G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators

21 June 2019

Papers citing "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators"

42 / 42 papers shown

Title
The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data Georgi Ganev Meenatchi Sundaram Muthu Selva Annamalai Sofiane Mahiou Emiliano De Cristofaro 24 2 0 09 Apr 2025
From Easy to Hard: Building a Shortcut for Differentially Private Image Synthesis Kecen Li Chen Gong Xiaochen Li Yuzhong Zhao Xinwen Hou Tianhao Wang 43 1 0 02 Apr 2025
VP-NTK: Exploring the Benefits of Visual Prompting in Differentially Private Data Synthesis Chia-Yi Hsu Jia-You Chen Yu-Lin Tsai Chih-Hsun Lin Pin-Yu Chen Chia-Mu Yu Chun-ying Huang 52 0 0 20 Mar 2025
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion Zhenheng Tang Yonggang Zhang Peijie Dong Y. Cheung Amelie Chi Zhou Bo Han Xiaowen Chu FedML MoMe AI4CE 53 6 0 27 Oct 2024
PFGuard: A Generative Framework with Privacy and Fairness Safeguards Soyeon Kim Yuji Roh Geon Heo Steven Euijong Whang 39 0 0 03 Oct 2024
Learning Privacy-Preserving Student Networks via Discriminative-Generative Distillation Shiming Ge Bochao Liu Pengju Wang Yong Li Dan Zeng FedML 44 9 0 04 Sep 2024
Learning Differentially Private Diffusion Models via Stochastic Adversarial Distillation Bochao Liu Pengju Wang Shiming Ge 46 1 0 27 Aug 2024
Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing Yongxin Guo Lin Wang Xiaoying Tang Tao R. Lin FedML OOD 29 0 0 25 May 2024
Privacy-Enhanced Database Synthesis for Benchmark Publishing (Technical Report) Yongrui Zhong Yunqing Ge Jianbin Qin Yongrui Zhong Bo Tang Yu-Xuan Qiu Rui Mao Ye Yuan Makoto Onizuka Chuan Xiao 34 0 0 02 May 2024
FedImpro: Measuring and Improving Client Update in Federated Learning Zhenheng Tang Yonggang Zhang S. Shi Xinmei Tian Tongliang Liu Bo Han Xiaowen Chu FedML 26 13 0 10 Feb 2024
Differentially Private Gradient Flow based on the Sliced Wasserstein Distance Ilana Sebag Muni Sreenivas Pydi Jean-Yves Franceschi Alain Rakotomamonjy Mike Gartrell Jamal Atif Alexandre Allauzen 24 2 0 13 Dec 2023
Hot PATE: Private Aggregation of Distributions for Diverse Task Edith Cohen Benjamin Cohen-Wang Xin Lyu Jelani Nelson Tamas Sarlos Uri Stemmer 52 3 0 04 Dec 2023
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning Zhiqin Yang Yonggang Zhang Yuxiang Zheng Xinmei Tian Hao Peng Tongliang Liu Bo Han FedML 30 61 0 08 Oct 2023
DPGOMI: Differentially Private Data Publishing with Gaussian Optimized Model Inversion Dongjie Chen S. Cheung Chen-Nee Chuah 16 0 0 06 Oct 2023
A Unified View of Differentially Private Deep Generative Modeling Dingfan Chen Raouf Kerkouche Mario Fritz SyDa 33 4 0 27 Sep 2023
Large-Scale Public Data Improves Differentially Private Image Generation Quality Ruihan Wu Chuan Guo Kamalika Chaudhuri 29 2 0 04 Aug 2023
Deep Generative Models, Synthetic Tabular Data, and Differential Privacy: An Overview and Synthesis Conor Hassan Roberto Salomone Kerrie Mengersen 28 6 0 28 Jul 2023
SoK: Privacy-Preserving Data Synthesis Yuzheng Hu Fan Wu Yue Liu Yunhui Long Gonzalo Munilla Garrido Chang Ge Bolin Ding David A. Forsyth Bo-wen Li D. Song 60 26 0 05 Jul 2023
Adversarial Robustness in Unsupervised Machine Learning: A Systematic Review Mathias Lundteigen Mohus Jinyue Li AAML 30 1 0 01 Jun 2023
Model Conversion via Differentially Private Data-Free Distillation Bochao Liu Pengju Wang Shikun Li Dan Zeng Shiming Ge FedML 21 3 0 25 Apr 2023
Differentially Private Synthetic Data Generation via Lipschitz-Regularised Variational Autoencoders Benedikt Groß Gerhard Wunder SyDa 26 2 0 22 Apr 2023
DPAF: Image Synthesis via Differentially Private Aggregation in Forward Phase Chih-Hsun Lin Chia-Yi Hsu Chia-Mu Yu Yang Cao Chun-ying Huang 36 1 0 20 Apr 2023
k-SALSA: k-anonymous synthetic averaging of retinal images via local style alignment Minkyu Jeon Hyeon-Jin Park Hyunwoo J. Kim Michael Morley Hyunghoon Cho MedIm 29 4 0 20 Mar 2023
Membership Inference Attacks against Synthetic Data through Overfitting Detection B. V. Breugel Hao Sun Zhaozhi Qian M. Schaar 33 45 0 24 Feb 2023
Machine Learning for Synthetic Data Generation: A Review Ying-Cheng Lu Minjie Shen Huazheng Wang Xiao Wang Capucine Van Rechem Tianfan Fu Wenqi Wei SyDa 42 140 0 08 Feb 2023
Private GANs, Revisited Alex Bie Gautam Kamath Guojun Zhang 38 14 0 06 Feb 2023
Differentially Private Kernel Inducing Points using features from ScatterNets (DP-KIP-ScatterNet) for Privacy Preserving Data Distillation Margarita Vinaroz M. Park DD 28 0 0 31 Jan 2023
Synthcity: facilitating innovative use cases of synthetic data in different data modalities Zhaozhi Qian B. Cebere M. Schaar SyDa 38 57 0 18 Jan 2023
On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulation Yucong Liu ChiHua Wang Guang Cheng 29 7 0 28 Nov 2022
DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder Bjarne Pfitzner B. Arnrich FedML 33 19 0 21 Nov 2022
Private Set Generation with Discriminative Information Dingfan Chen Raouf Kerkouche Mario Fritz DD 30 34 0 07 Nov 2022
In Differential Privacy, There is Truth: On Vote Leakage in Ensemble Private Learning Jiaqi Wang R. Schuster Ilia Shumailov David Lie Nicolas Papernot FedML 33 3 0 22 Sep 2022
DP $^2$ -VAE: Differentially Private Pre-trained Variational Autoencoders Dihong Jiang Guojun Zhang Mahdi Karami Xi Chen Yunfeng Shao Yaoliang Yu 49 15 0 05 Aug 2022
Privacy-Preserving Federated Recurrent Neural Networks Sinem Sav Abdulrahman Diaa Apostolos Pyrgelis Jean-Philippe Bossuat Jean-Pierre Hubaux 15 7 0 28 Jul 2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning Zhenheng Tang Yonggang Zhang S. Shi Xinfu He Bo Han Xiaowen Chu FedML 32 73 0 06 Jun 2022
Noise-Aware Statistical Inference with Differentially Private Synthetic Data Ossi Raisa Joonas Jälkö Samuel Kaski Antti Honkela SyDa 43 10 0 28 May 2022
Synthetic Data -- what, why and how? James Jordon Lukasz Szpruch F. Houssiau M. Bottarelli Giovanni Cherubin Carsten Maple Samuel N. Cohen Adrian Weller 46 109 0 06 May 2022
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning Chuan Ma Jun Li Kang Wei Bo Liu Ming Ding Long Yuan Zhu Han H. Vincent Poor 57 42 0 18 Feb 2022
NeuroMixGDP: A Neural Collapse-Inspired Random Mixup for Private Data Release Donghao Li Yang Cao Yuan Yao 35 2 0 14 Feb 2022
FedMed-GAN: Federated Domain Translation on Unsupervised Cross-Modality Brain Image Synthesis Jinbao Wang Guoyang Xie Yawen Huang Yuexiang Li Yefeng Zheng Feng Zheng Yaochu Jin FedML MedIm 48 47 0 22 Jan 2022
DP-SGD vs PATE: Which Has Less Disparate Impact on GANs? Georgi Ganev 15 5 0 26 Nov 2021
SEDML: Securely and Efficiently Harnessing Distributed Knowledge in Machine Learning Yansong Gao Qun Li Yifeng Zheng Guohong Wang Jiannan Wei Mang Su 32 3 0 26 Oct 2021