Fast Dimension Independent Private AdaGrad on Publicly Estimated
Subspaces

Fast Dimension Independent Private AdaGrad on Publicly Estimated Subspaces

14 August 2020

Abhradeep Thakurta

Papers citing "Fast Dimension Independent Private AdaGrad on Publicly Estimated Subspaces"

10 / 10 papers shown

Title
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs Charlie Hou Akshat Shrivastava Hongyuan Zhan Rylan Conway Trang Le Adithya Sagar Giulia Fanti Daniel Lazar 36 8 0 05 Jun 2024
On Differentially Private Subspace Estimation in a Distribution-Free Setting Eliad Tsfadia 25 1 0 09 Feb 2024
Choosing Public Datasets for Private Machine Learning via Gradient Subspace Distance Xin Gu Gautam Kamath Zhiwei Steven Wu 28 12 0 02 Mar 2023
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics A. Banerjee Tiancong Chen Xinyan Li Yingxue Zhou 34 8 0 09 Jan 2022
Public Data-Assisted Mirror Descent for Private Model Training Ehsan Amid Arun Ganesh Rajiv Mathews Swaroop Indra Ramaswamy Shuang Song Thomas Steinke Vinith Suriyakumar Om Thakkar Abhradeep Thakurta 13 49 0 01 Dec 2021
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 187 412 0 14 Jul 2021
Private Adaptive Gradient Methods for Convex Optimization Hilal Asi John C. Duchi Alireza Fallah O. Javidbakht Kunal Talwar 16 53 0 25 Jun 2021
Large Scale Private Learning via Low-rank Reparametrization Da Yu Huishuai Zhang Wei Chen Jian Yin Tie-Yan Liu 23 100 0 17 Jun 2021
The Power of Sampling: Dimension-free Risk Bounds in Private ERM Yin Tat Lee Daogao Liu Zhou Lu 22 3 0 28 May 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning Da Yu Huishuai Zhang Wei Chen Tie-Yan Liu FedML SILM 94 110 0 25 Feb 2021