Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms

21 January 2023

Papers citing "Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms"

5 / 5 papers shown

Title
Neural Collapse Meets Differential Privacy: Curious Behaviors of NoisyGD with Near-perfect Representation Learning Chendi Wang Yuqing Zhu Weijie J. Su Yu-Xiang Wang AAML 58 4 0 14 May 2024
Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data Yvonne Zhou Mingyu Liang Ivan Brugere Dana Dachman-Soled Danial Dervovic Antigoni Polychroniadou Min Wu 26 1 0 06 Feb 2024
A Survey on Statistical Theory of Deep Learning: Approximation, Training Dynamics, and Generative Models Namjoon Suh Guang Cheng MedIm 32 13 0 14 Jan 2024
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via $f$ -Differential Privacy Chendi Wang Buxin Su Jiayuan Ye Reza Shokri Weijie J. Su FedML 21 10 0 30 Oct 2023
Utility Theory of Synthetic Data Generation Shi Xu W. Sun Guang Cheng 31 5 0 17 May 2023