How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization

17 February 2024

Papers citing "How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization"

20 / 20 papers shown

Title
Adaptive Batch Size for Privately Finding Second-Order Stationary Points Daogao Liu Kunal Talwar 396 0 0 10 Oct 2024
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks Arun Ganesh Daogao Liu Sewoong Oh Abhradeep Thakurta ODL 72 13 0 20 Feb 2023
Momentum Aggregation for Private Non-convex ERM Hoang Tran Ashok Cutkosky 66 14 0 12 Oct 2022
Private Non-Convex Federated Learning Without a Trusted Server Andrew Lowy Ali Ghafelebashi Meisam Razaviyayn FedML 62 27 0 13 Mar 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 80 51 0 01 Dec 2021
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 230 367 0 13 Oct 2021
Non-Euclidean Differentially Private Stochastic Convex Optimization: Optimal Rates in Linear Time Raef Bassily Cristóbal Guzmán Anupama Nandi 103 68 0 01 Mar 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown Basel Alomair Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 489 1,923 0 14 Dec 2020
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds Yingxue Zhou Xiangyi Chen Mingyi Hong Zhiwei Steven Wu A. Banerjee 65 25 0 24 Jun 2020
Private Stochastic Convex Optimization: Optimal Rates in Linear Time Vitaly Feldman Tomer Koren Kunal Talwar 58 209 0 10 May 2020
Loss landscapes and optimization in over-parameterized non-linear systems and neural networks Chaoyue Liu Libin Zhu M. Belkin ODL 77 262 0 29 Feb 2020
Private Stochastic Convex Optimization with Optimal Rates Raef Bassily Vitaly Feldman Kunal Talwar Abhradeep Thakurta 78 242 0 27 Aug 2019
Robust Bi-Tempered Logistic Loss Based on Bregman Divergences Ehsan Amid Manfred K. Warmuth Rohan Anil Tomer Koren NoLa 42 129 0 08 Jun 2019
SGD Converges to Global Minimum in Deep Learning via Star-convex Path Yi Zhou Junjie Yang Huishuai Zhang Yingbin Liang Vahid Tarokh 58 74 0 02 Jan 2019
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD Zeyuan Allen-Zhu ODL 73 171 0 08 Jan 2018
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 261 4,135 0 18 Oct 2016
Gradient Descent Learns Linear Dynamical Systems Moritz Hardt Tengyu Ma Benjamin Recht 107 240 0 16 Sep 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 213 6,130 0 01 Jul 2016
Matrix Completion has No Spurious Local Minimum Rong Ge Jason D. Lee Tengyu Ma 108 599 0 24 May 2016
A Geometric Analysis of Phase Retrieval Ju Sun Qing Qu John N. Wright 127 526 0 22 Feb 2016