Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget

28 August 2018

Papers citing "Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget"

13 / 13 papers shown

Title
Layered Randomized Quantization for Communication-Efficient and Privacy-Preserving Distributed Learning Guangfeng Yan Tan Li Tian-Shing Lan Kui Wu Linqi Song 19 6 0 12 Dec 2023
Adap DP-FL: Differentially Private Federated Learning with Adaptive Noise Jie Fu Zhili Chen Xiao Han FedML 17 28 0 29 Nov 2022
SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing Jie Fu Zhili Chen Xinpeng Ling 19 0 0 14 Nov 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Y. Yang 39 20 0 18 Oct 2022
Adaptive Differentially Private Empirical Risk Minimization Xiaoxia Wu Lingxiao Wang Irina Cristali Quanquan Gu Rebecca Willett 26 6 0 14 Oct 2021
Efficient Hyperparameter Optimization for Differentially Private Deep Learning Aman Priyanshu Rakshit Naidu Fatemehsadat Mireshghallah Mohammad Malekzadeh 19 5 0 09 Aug 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 17 71 0 04 Jul 2021
Differentially private inference via noisy optimization Marco Avella-Medina Casey Bradshaw Po-Ling Loh FedML 25 29 0 19 Mar 2021
Stochastic Adaptive Line Search for Differentially Private Optimization Chen Chen Jaewoo Lee 14 14 0 18 Aug 2020
User-Level Privacy-Preserving Federated Learning: Analysis and Performance Optimization Kang Wei Jun Li Ming Ding Chuan Ma Hang Su Bo-Wen Zhang H. Vincent Poor FedML 25 11 0 29 Feb 2020
An Adaptive and Fast Convergent Approach to Differentially Private Deep Learning Zhiying Xu Shuyu Shi A. Liu Jun Zhao Lin Chen FedML 16 36 0 19 Dec 2019
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 26 121 0 04 Jun 2019
A Hybrid Approach to Privacy-Preserving Federated Learning Stacey Truex Nathalie Baracaldo Ali Anwar Thomas Steinke Heiko Ludwig Rui Zhang Yi Zhou FedML 4 882 0 07 Dec 2018