PEARL: Data Synthesis via Private Embeddings and Adversarial
Reconstruction Learning

PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning

8 June 2021

Tsubasa Takahashi

Papers citing "PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning"

9 / 9 papers shown

Title
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 50 0 0 20 Mar 2025
Transfer Learning with Pre-trained Conditional Generative Models Shinýa Yamaguchi Sekitoshi Kanai Atsutoshi Kumagai Daiki Chijiwa H. Kashima VLM CLL BDL DiffM 132 5 0 21 Feb 2025
RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models Tanqiu Jiang Changjiang Li Fenglong Ma Ting Wang 59 0 0 18 Feb 2025
PFGuard: A Generative Framework with Privacy and Fairness Safeguards Soyeon Kim Yuji Roh Geon Heo Steven Euijong Whang 33 0 0 03 Oct 2024
NetDPSyn: Synthesizing Network Traces under Differential Privacy Danyu Sun Joann Qiongna Chen Chen Gong Tianhao Wang Zhou Li 52 1 0 08 Sep 2024
PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretraining Kecen Li Chen Gong Zhixiang Li Yuzhong Zhao Xinwen Hou Tianhao Wang 25 10 0 19 Oct 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 21 7 0 28 Nov 2022
Noise-Aware Statistical Inference with Differentially Private Synthetic Data Ossi Raisa Joonas Jälkö Samuel Kaski Antti Honkela SyDa 34 10 0 28 May 2022
G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators Yunhui Long Boxin Wang Zhuolin Yang B. Kailkhura Aston Zhang C.A. Gunter Bo-wen Li 14 72 0 21 Jun 2019