Differentially Private SGDA for Minimax Problems

Differentially Private SGDA for Minimax Problems

22 January 2022

Kush R. Varshney

Papers citing "Differentially Private SGDA for Minimax Problems"

16 / 16 papers shown

Title
Stability and Generalization in Free Adversarial Training Xiwei Cheng Kexin Fu Farzan Farnia AAML 42 2 0 08 Jan 2025
Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems Tomás González Cristóbal Guzmán Courtney Paquette 32 3 0 05 Mar 2024
Differentially Private Worst-group Risk Minimization Xinyu Zhou Raef Bassily 25 2 0 29 Feb 2024
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates Michael Menart Enayat Ullah Raman Arora Raef Bassily Cristóbal Guzmán 30 2 0 22 Nov 2023
Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm Miaoxi Zhu Li Shen Bo Du Dacheng Tao 13 6 0 31 Oct 2023
Fairness-aware Federated Minimax Optimization with Convergence Guarantee Gerry Windiarto Mohamad Dunda Shenghui Song FedML 14 1 0 10 Jul 2023
Fairness-aware Differentially Private Collaborative Filtering Zhenhuan Yang Yingqiang Ge Congzhe Su Dingxian Wang Xiaoting Zhao Yiming Ying FedML 19 3 0 16 Mar 2023
Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap Raef Bassily Cristóbal Guzmán Michael Menart FedML 29 4 0 24 Feb 2023
Stochastic Differentially Private and Fair Learning Andrew Lowy Devansh Gupta Meisam Razaviyayn FaML FedML 14 13 0 17 Oct 2022
What is a Good Metric to Study Generalization of Minimax Learners? Asuman Ozdaglar S. Pattathil Jiawei Zhang K. Zhang 9 13 0 09 Jun 2022
Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization Liang Zhang K. K. Thekumparampil Sewoong Oh Niao He 33 17 0 01 Jun 2022
Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization Siqi Zhang Yifan Hu Liang Zhang Niao He 22 3 0 28 May 2022
Fair Federated Learning via Bounded Group Loss Shengyuan Hu Zhiwei Steven Wu Virginia Smith FaML FedML 11 14 0 18 Mar 2022
Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization Canzhe Zhao Yanjie Ze Jing Dong Baoxiang Wang Shuai Li 39 4 0 25 Jan 2022
Optimal Algorithms for Differentially Private Stochastic Monotone Variational Inequalities and Saddle-Point Problems Digvijay Boob Cristóbal Guzmán 20 15 0 07 Apr 2021
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 119 1,194 0 16 Aug 2016