Differentially Private SGD with Non-Smooth Losses

22 January 2021

Papers citing "Differentially Private SGD with Non-Smooth Losses"

9 / 9 papers shown

Title
Stability and Generalization for Markov Chain Stochastic Gradient Methods Puyu Wang Yunwen Lei Yiming Ying Ding-Xuan Zhou 24 18 0 16 Sep 2022
Differentially Private Stochastic Gradient Descent with Low-Noise Puyu Wang Yunwen Lei Yiming Ying Ding-Xuan Zhou FedML 49 5 0 09 Sep 2022
Sharper Utility Bounds for Differentially Private Models Yilin Kang Yong Liu Jian Li Weiping Wang FedML 35 3 0 22 Apr 2022
Differentially Private SGDA for Minimax Problems Zhenhuan Yang Shu Hu Yunwen Lei Kush R. Varshney Siwei Lyu Yiming Ying 36 19 0 22 Jan 2022
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization Paul Mangold A. Bellet Joseph Salmon Marc Tommasi 32 14 0 22 Oct 2021
Stability and Generalization for Randomized Coordinate Descent Puyu Wang Liang Wu Yunwen Lei 27 7 0 17 Aug 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 26 13 0 19 Jul 2021
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark W. Schmidt Francis R. Bach 128 259 0 10 Dec 2012
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 104 571 0 08 Dec 2012