Private Stochastic Convex Optimization: Optimal Rates in Linear Time

10 May 2020

Papers citing "Private Stochastic Convex Optimization: Optimal Rates in Linear Time"

36 / 136 papers shown

Title
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
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings Raef Bassily Cristóbal Guzmán Michael Menart 49 55 0 12 Jul 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
Shuffle Private Stochastic Convex Optimization Albert Cheu Matthew Joseph Jieming Mao Binghui Peng FedML 31 25 0 17 Jun 2021
Stochastic Bias-Reduced Gradient Methods Hilal Asi Y. Carmon A. Jambulapati Yujia Jin Aaron Sidford 24 29 0 17 Jun 2021
On the Convergence of Differentially Private Federated Learning on Non-Lipschitz Objectives, and with Normalized Client Updates Rudrajit Das Abolfazl Hashemi Sujay Sanghavi Inderjit S. Dhillon FedML 48 4 0 13 Jun 2021
The Power of Sampling: Dimension-free Risk Bounds in Private ERM Yin Tat Lee Daogao Liu Zhou Lu 24 3 0 28 May 2021
Optimal Algorithms for Differentially Private Stochastic Monotone Variational Inequalities and Saddle-Point Problems Digvijay Boob Cristóbal Guzmán 28 15 0 07 Apr 2021
Optimal Query Complexity of Secure Stochastic Convex Optimization Wei Tang Chien-Ju Ho Yang Liu 27 4 0 05 Apr 2021
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps Janardhan Kulkarni Y. Lee Daogao Liu 13 28 0 29 Mar 2021
Differentially private inference via noisy optimization Marco Avella-Medina Casey Bradshaw Po-Ling Loh FedML 42 29 0 19 Mar 2021
$Private Stochastic Convex Optimization: Optimal Rates in $\ell_1$ Geometry$ Private Stochastic Convex Optimization: Optimal Rates in $\ell_1$ Geometry Hilal Asi Vitaly Feldman Tomer Koren Kunal Talwar 25 91 0 02 Mar 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
Learning with User-Level Privacy Daniel Levy Ziteng Sun Kareem Amin Satyen Kale Alex Kulesza M. Mohri A. Suresh FedML 32 89 0 23 Feb 2021
Deep Learning with Label Differential Privacy Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Chiyuan Zhang 42 146 0 11 Feb 2021
Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent R. Chourasia Jiayuan Ye Reza Shokri FedML 30 69 0 11 Feb 2021
Stability of SGD: Tightness Analysis and Improved Bounds Yikai Zhang Wenjia Zhang Sammy Bald Vamsi Pingali Chao Chen Mayank Goswami MLT 27 36 0 10 Feb 2021
Local and Global Uniform Convexity Conditions Thomas Kerdreux Alexandre d’Aspremont Sebastian Pokutta 17 12 0 09 Feb 2021
Algorithmic Instabilities of Accelerated Gradient Descent Amit Attia Tomer Koren 16 8 0 03 Feb 2021
Differentially Private SGD with Non-Smooth Losses Puyu Wang Yunwen Lei Yiming Ying Hai Zhang 18 28 0 22 Jan 2021
Dynamic Privacy Budget Allocation Improves Data Efficiency of Differentially Private Gradient Descent Junyuan Hong Zhangyang Wang Jiayu Zhou 11 9 0 19 Jan 2021
Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning Milad Nasr Shuang Song Abhradeep Thakurta Nicolas Papernot Nicholas Carlini MIACV FedML 82 216 0 11 Jan 2021
Contraction of $E_γ$ -Divergence and Its Applications to Privacy S. Asoodeh Mario Díaz Flavio du Pin Calmon 39 0 0 20 Dec 2020
Robust and Private Learning of Halfspaces Badih Ghazi Ravi Kumar Pasin Manurangsi Thao Nguyen 17 10 0 30 Nov 2020
Stochastic Adaptive Line Search for Differentially Private Optimization Chen Chen Jaewoo Lee 22 14 0 18 Aug 2020
Fast Dimension Independent Private AdaGrad on Publicly Estimated Subspaces Peter Kairouz Mónica Ribero Keith Rush Abhradeep Thakurta 93 14 0 14 Aug 2020
Breaking the Communication-Privacy-Accuracy Trilemma Wei-Ning Chen Peter Kairouz Ayfer Özgür 14 116 0 22 Jul 2020
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds Yingxue Zhou Xiangyi Chen Mingyi Hong Zhiwei Steven Wu A. Banerjee 24 25 0 24 Jun 2020
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses Raef Bassily Vitaly Feldman Cristóbal Guzmán Kunal Talwar MLT 24 192 0 12 Jun 2020
Evading Curse of Dimensionality in Unconstrained Private GLMs via Private Gradient Descent Shuang Song Thomas Steinke Om Thakkar Abhradeep Thakurta 35 50 0 11 Jun 2020
Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives R. Arora T. V. Marinov Enayat Ullah 23 1 0 22 Feb 2020
Data Heterogeneity Differential Privacy: From Theory to Algorithm Yilin Kang Jian Li Yong Liu Weiping Wang 28 1 0 20 Feb 2020
Efficient Privacy-Preserving Stochastic Nonconvex Optimization Lingxiao Wang Bargav Jayaraman David Evans Quanquan Gu 19 28 0 30 Oct 2019
Private Identity Testing for High-Dimensional Distributions C. Canonne Gautam Kamath Audra McMillan Jonathan R. Ullman Lydia Zakynthinou 37 36 0 28 May 2019
Learning Privately with Labeled and Unlabeled Examples A. Beimel Kobbi Nissim Uri Stemmer 40 23 0 10 Jul 2014
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 104 572 0 08 Dec 2012