$Private Stochastic Convex Optimization: Optimal Rates in $\ell_1$ Geometry$

Private Stochastic Convex Optimization: Optimal Rates in $\ell_1$ Geometry

2 March 2021

Papers citing "Private Stochastic Convex Optimization: Optimal Rates in $\ell_1$ Geometry"

20 / 20 papers shown

Title
Adaptive Batch Size for Privately Finding Second-Order Stationary Points Daogao Liu Kunal Talwar 180 0 0 10 Oct 2024
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates Puning Zhao Xiaogang Xu Zhe Liu Chong Wang Rongfei Fan Qingming Li 48 1 0 19 Aug 2024
Private Online Learning via Lazy Algorithms Hilal Asi Tomer Koren Daogao Liu Kunal Talwar 109 0 0 05 Jun 2024
Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited Jinyan Su Changhong Zhao Di Wang 33 3 0 31 Mar 2023
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks Arun Ganesh Daogao Liu Sewoong Oh Abhradeep Thakurta ODL 27 12 0 20 Feb 2023
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler Sivakanth Gopi Y. Lee Daogao Liu Ruoqi Shen Kevin Tian 17 7 0 13 Feb 2023
Near Optimal Private and Robust Linear Regression Xiyang Liu Prateek Jain Weihao Kong Sewoong Oh A. Suggala 41 9 0 30 Jan 2023
ReSQueing Parallel and Private Stochastic Convex Optimization Y. Carmon A. Jambulapati Yujia Jin Y. Lee Daogao Liu Aaron Sidford Kevin Tian FedML 28 12 0 01 Jan 2023
Optimal Algorithms for Stochastic Complementary Composite Minimization Alexandre d’Aspremont Cristóbal Guzmán Clément Lezane 33 3 0 03 Nov 2022
Private optimization in the interpolation regime: faster rates and hardness results Hilal Asi Karan N. Chadha Gary Cheng John C. Duchi 47 5 0 31 Oct 2022
Private Online Prediction from Experts: Separations and Faster Rates Hilal Asi Vitaly Feldman Tomer Koren Kunal Talwar FedML 32 18 0 24 Oct 2022
Uniform Stability for First-Order Empirical Risk Minimization Amit Attia Tomer Koren 20 5 0 17 Jul 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
Beyond Uniform Lipschitz Condition in Differentially Private Optimization Rudrajit Das Satyen Kale Zheng Xu Tong Zhang Sujay Sanghavi 26 17 0 21 Jun 2022
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization Paul Mangold A. Bellet Joseph Salmon Marc Tommasi 32 14 0 22 Oct 2021
Private Adaptive Gradient Methods for Convex Optimization Hilal Asi John C. Duchi Alireza Fallah O. Javidbakht Kunal Talwar 19 53 0 25 Jun 2021
Stochastic Bias-Reduced Gradient Methods Hilal Asi Y. Carmon A. Jambulapati Yujia Jin Aaron Sidford 24 29 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
Non-Euclidean Differentially Private Stochastic Convex Optimization: Optimal Rates in Linear Time Raef Bassily Cristóbal Guzmán Anupama Nandi 54 66 0 01 Mar 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