Dimension Independent Generalization of DP-SGD for Overparameterized
Smooth Convex Optimization

Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization

3 June 2022

Tong Zhang

Papers citing "Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization"

8 / 8 papers shown

Title
A Theoretical Survey on Foundation Models Shi Fu Yuzhu Chen Yingjie Wang Dacheng Tao 28 0 0 15 Oct 2024
Pre-training Differentially Private Models with Limited Public Data Zhiqi Bu Xinwei Zhang Mingyi Hong Sheng Zha George Karypis 79 3 0 28 Feb 2024
DPZero: Private Fine-Tuning of Language Models without Backpropagation Liang Zhang Bingcong Li K. K. Thekumparampil Sewoong Oh Niao He 28 11 0 14 Oct 2023
Lower Generalization Bounds for GD and SGD in Smooth Stochastic Convex Optimization Peiyuan Zhang Jiaye Teng Junzhe Zhang 39 4 0 19 Mar 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping Jiyan He Xuechen Li Da Yu Huishuai Zhang Janardhan Kulkarni Y. Lee A. Backurs Nenghai Yu Jiang Bian 27 46 0 03 Dec 2022
When Does Differentially Private Learning Not Suffer in High Dimensions? Xuechen Li Daogao Liu Tatsunori Hashimoto Huseyin A. Inan Janardhan Kulkarni Y. Lee Abhradeep Thakurta 34 58 0 01 Jul 2022
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint Y. Freund Yi Ma Tong Zhang 37 16 0 05 Oct 2021
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 101 570 0 08 Dec 2012