Differentially Private Image Classification from Features

Differentially Private Image Classification from Features

24 November 2022

Abhradeep Thakurta

Papers citing "Differentially Private Image Classification from Features"

14 / 14 papers shown

Title
Differentially Private Prototypes for Imbalanced Transfer Learning Dariush Wahdany Matthew Jagielski Adam Dziedzic Franziska Boenisch 80 0 0 17 Feb 2025
Unlocking Accuracy and Fairness in Differentially Private Image Classification Leonard Berrada Soham De J. Shen Jamie Hayes Robert Stanforth David Stutz Pushmeet Kohli Samuel L. Smith Borja Balle 19 13 0 21 Aug 2023
Differentially Private Image Classification by Learning Priors from Random Processes Xinyu Tang Ashwinee Panda Vikash Sehwag Prateek Mittal 13 20 0 08 Jun 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 94 167 0 01 Mar 2023
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization Ashwinee Panda Xinyu Tang Saeed Mahloujifar Vikash Sehwag Prateek Mittal 24 11 0 08 Dec 2022
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent Da Yu Gautam Kamath Janardhan Kulkarni Tie-Yan Liu Jian Yin Huishuai Zhang 4 17 0 06 Jun 2022
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy Zhiqi Bu J. Mao Shiyun Xu 131 47 0 21 May 2022
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 134 344 0 13 Oct 2021
Not all noise is accounted equally: How differentially private learning benefits from large sampling rates Friedrich Dörmann Osvald Frisk L. Andersen Christian Fischer Pedersen FedML 44 25 0 12 Oct 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 239 2,592 0 04 May 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning Da Yu Huishuai Zhang Wei Chen Tie-Yan Liu FedML SILM 91 110 0 25 Feb 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 267 1,808 0 14 Dec 2020
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 134 420 0 29 Nov 2018
Efficient Per-Example Gradient Computations Ian Goodfellow 169 73 0 07 Oct 2015