Differentially Private Learning with Per-Sample Adaptive Clipping

1 December 2022

Papers citing "Differentially Private Learning with Per-Sample Adaptive Clipping"

40 / 40 papers shown

Title
PCDP-SGD: Improving the Convergence of Differentially Private SGD via Projection in Advance Haichao Sha Ruixuan Liu Yi-xiao Liu Hong Chen 78 1 0 06 Dec 2023
SSVMR: Saliency-based Self-training for Video-Music Retrieval Xuxin Cheng Zhihong Zhu Hongxiang Li Yaowei Li Yuexian Zou 50 29 0 18 Feb 2023
M3ST: Mix at Three Levels for Speech Translation Xuxin Cheng Qianqian Dong Fengpeng Yue Tom Ko Mingxuan Wang Yuexian Zou 62 41 0 07 Dec 2022
A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding Zhihong Zhu Weiyuan Xu Xuxin Cheng Tengtao Song Yuexian Zou 57 23 0 08 Nov 2022
Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization Xiaodong Yang Huishuai Zhang Wei Chen Tie-Yan Liu 52 38 0 27 Jun 2022
Disparate Impact in Differential Privacy from Gradient Misalignment Maria S. Esipova Atiyeh Ashari Ghomi Yaqiao Luo Jesse C. Cresswell 50 29 0 15 Jun 2022
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger Zhiqi Bu Yu Wang Sheng Zha George Karypis 97 71 0 14 Jun 2022
Differentially private training of residual networks with scale normalisation Helena Klause Alexander Ziller Daniel Rueckert Kerstin Hammernik Georgios Kaissis 51 33 0 01 Mar 2022
Private Adaptive Optimization with Side Information Tian Li Manzil Zaheer Sashank J. Reddi Virginia Smith 64 36 0 12 Feb 2022
Toward Training at ImageNet Scale with Differential Privacy Alexey Kurakin Shuang Song Steve Chien Roxana Geambasu Andreas Terzis Abhradeep Thakurta 63 102 0 28 Jan 2022
Dynamic Differential-Privacy Preserving SGD Jian Du Song Li Xiangyi Chen Siheng Chen Mingyi Hong 45 33 0 30 Oct 2021
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization Paul Mangold A. Bellet Joseph Salmon Marc Tommasi 67 14 0 22 Oct 2021
Adaptive Differentially Private Empirical Risk Minimization Xiaoxia Wu Lingxiao Wang Irina Cristali Quanquan Gu Rebecca Willett 102 6 0 14 Oct 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 207 364 0 13 Oct 2021
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 160 124 0 07 Oct 2021
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 267 363 0 25 Sep 2021
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings Raef Bassily Cristóbal Guzmán Michael Menart 63 56 0 12 Jul 2021
Private Adaptive Gradient Methods for Convex Optimization Hilal Asi John C. Duchi Alireza Fallah O. Javidbakht Kunal Talwar 51 53 0 25 Jun 2021
Large Scale Private Learning via Low-rank Reparametrization Da Yu Huishuai Zhang Wei Chen Jian Yin Tie-Yan Liu 50 103 0 17 Jun 2021
Differentially Private SGD with Non-Smooth Losses Puyu Wang Yunwen Lei Yiming Ying Hai Zhang 41 28 0 22 Jan 2021
Improved Analysis of Clipping Algorithms for Non-convex Optimization Bohang Zhang Jikai Jin Cong Fang Liwei Wang 74 92 0 05 Oct 2020
Differentially Private Accelerated Optimization Algorithms Nurdan Kuru cS. .Ilker Birbil Mert Gurbuzbalaban S. Yıldırım 59 23 0 05 Aug 2020
Tempered Sigmoid Activations for Deep Learning with Differential Privacy Nicolas Papernot Abhradeep Thakurta Shuang Song Steve Chien Ulfar Erlingsson AAML 174 179 0 28 Jul 2020
Supervised Contrastive Learning Prannay Khosla Piotr Teterwak Chen Wang Aaron Sarna Yonglong Tian Phillip Isola Aaron Maschinot Ce Liu Dilip Krishnan SSL 139 4,520 0 23 Apr 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 323 18,686 0 13 Feb 2020
Gradient Perturbation is Underrated for Differentially Private Convex Optimization Da Yu Huishuai Zhang Kwei-Herng Lai Yuening Li Xia Hu 45 37 0 26 Nov 2019
AdaCliP: Adaptive Clipping for Private SGD Venkatadheeraj Pichapati A. Suresh Felix X. Yu Sashank J. Reddi Sanjiv Kumar 45 124 0 20 Aug 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 90 2,199 0 21 Jun 2019
Why gradient clipping accelerates training: A theoretical justification for adaptivity J.N. Zhang Tianxing He S. Sra Ali Jadbabaie 72 459 0 28 May 2019
Differentially Private Learning with Adaptive Clipping Galen Andrew Om Thakkar H. B. McMahan Swaroop Ramaswamy FedML 57 339 0 09 May 2019
Three Tools for Practical Differential Privacy K. V. D. Veen Ruben Seggers Peter Bloem Giorgio Patrini 36 39 0 07 Dec 2018
Differentially Private Empirical Risk Minimization Revisited: Faster and More General Di Wang Minwei Ye Jinhui Xu 112 273 0 14 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 244 8,856 0 25 Aug 2017
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference Adina Williams Nikita Nangia Samuel R. Bowman 495 4,473 0 18 Apr 2017
Renyi Differential Privacy Ilya Mironov 77 1,253 0 24 Feb 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 189 6,101 0 01 Jul 2016
SQuAD: 100,000+ Questions for Machine Comprehension of Text Pranav Rajpurkar Jian Zhang Konstantin Lopyrev Percy Liang RALM 229 8,113 0 16 Jun 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.9K 193,426 0 10 Dec 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 224 8,391 0 28 Nov 2014
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming Saeed Ghadimi Guanghui Lan ODL 120 1,547 0 22 Sep 2013