Stochastic Differentially Private and Fair Learning

Stochastic Differentially Private and Fair Learning

17 October 2022

Meisam Razaviyayn

Papers citing "Stochastic Differentially Private and Fair Learning"

11 / 11 papers shown

Title
Learning with Differentially Private (Sliced) Wasserstein Gradients Clément Lalanne Jean-Michel Loubes David Rodríguez-Vítores FedML 41 0 0 03 Feb 2025
PFGuard: A Generative Framework with Privacy and Fairness Safeguards Soyeon Kim Yuji Roh Geon Heo Steven Euijong Whang 31 0 0 03 Oct 2024
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses Changyu Gao Andrew Lowy Xingyu Zhou Stephen J. Wright FedML 24 2 0 12 Jul 2024
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 Fair Binary Classifications Hrad Ghoukasian S. Asoodeh FaML 19 1 0 23 Feb 2024
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization Andrew Lowy Jonathan R. Ullman Stephen J. Wright 41 6 0 17 Feb 2024
Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning Kangkang Sun Xiaojin Zhang Xi Lin Gaolei Li Jing Wang Jianhua Li 25 4 0 30 Nov 2023
Privacy and Fairness in Federated Learning: on the Perspective of Trade-off Huiqiang Chen Tianqing Zhu Tao Zhang Wanlei Zhou Philip S. Yu FedML 17 43 0 25 Jun 2023
Private Stochastic Optimization With Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses Andrew Lowy Meisam Razaviyayn 30 13 0 15 Sep 2022
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent Da Yu Gautam Kamath Janardhan Kulkarni Tie-Yan Liu Jian Yin Huishuai Zhang 4 17 0 06 Jun 2022
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 267 1,808 0 14 Dec 2020