Differentially Private Image Classification from Features

24 November 2022

Papers citing "Differentially Private Image Classification from Features"

50 / 61 papers shown

Title
Fine-Tuning with Differential Privacy Necessitates an Additional Hyperparameter Search Yannis Cattan Christopher A. Choquette-Choo Nicolas Papernot Abhradeep Thakurta 35 21 0 05 Oct 2022
Recycling Scraps: Improving Private Learning by Leveraging Intermediate Checkpoints Virat Shejwalkar Arun Ganesh Rajiv Mathews Om Thakkar Abhradeep Thakurta 48 8 0 04 Oct 2022
Differentially Private Optimization on Large Model at Small Cost Zhiqi Bu Yu Wang Sheng Zha George Karypis 62 52 0 30 Sep 2022
Differentially Private Bias-Term Fine-tuning of Foundation Models Zhiqi Bu Yu Wang Sheng Zha George Karypis 56 47 0 30 Sep 2022
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization Xingyou Song Sagi Perel Chansoo Lee Greg Kochanski Daniel Golovin 75 27 0 27 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 47 58 0 01 Jul 2022
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger Zhiqi Bu Yu Wang Sheng Zha George Karypis 75 70 0 14 Jun 2022
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy Zhiqi Bu Jialin Mao Shiyun Xu 152 49 0 21 May 2022
CoCa: Contrastive Captioners are Image-Text Foundation Models Jiahui Yu Zirui Wang Vijay Vasudevan Legg Yeung Mojtaba Seyedhosseini Yonghui Wu VLM CLIP OffRL 116 1,279 0 04 May 2022
Unlocking High-Accuracy Differentially Private Image Classification through Scale Soham De Leonard Berrada Jamie Hayes Samuel L. Smith Borja Balle 53 223 0 28 Apr 2022
Mixed Differential Privacy in Computer Vision Aditya Golatkar Alessandro Achille Yu Wang Aaron Roth Michael Kearns Stefano Soatto PICV VLM 53 49 0 22 Mar 2022
Differentially private training of residual networks with scale normalisation Helena Klause Alexander Ziller Daniel Rueckert Kerstin Hammernik Georgios Kaissis 30 32 0 01 Mar 2022
Toward Training at ImageNet Scale with Differential Privacy Alexey Kurakin Shuang Song Steve Chien Roxana Geambasu Andreas Terzis Abhradeep Thakurta 48 101 0 28 Jan 2022
Reconstructing Training Data with Informed Adversaries Borja Balle Giovanni Cherubin Jamie Hayes MIACV AAML 69 162 0 13 Jan 2022
Differential privacy and robust statistics in high dimensions Xiyang Liu Weihao Kong Sewoong Oh 17 66 0 12 Nov 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 171 356 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 66 25 0 12 Oct 2021
Large-Scale Differentially Private BERT Rohan Anil Badih Ghazi Vineet Gupta Ravi Kumar Pasin Manurangsi 48 133 0 03 Aug 2021
Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates Steve Chien Prateek Jain Walid Krichene Steffen Rendle Shuang Song Abhradeep Thakurta Li Zhang 37 19 0 20 Jul 2021
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers Andreas Steiner Alexander Kolesnikov Xiaohua Zhai Ross Wightman Jakob Uszkoreit Lucas Beyer ViT 93 623 0 18 Jun 2021
Scaling Vision Transformers Xiaohua Zhai Alexander Kolesnikov N. Houlsby Lucas Beyer ViT 107 1,074 0 08 Jun 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 376 2,638 0 04 May 2021
Differentially private inference via noisy optimization Marco Avella-Medina Casey Bradshaw Po-Ling Loh FedML 63 29 0 19 Mar 2021
Wide Network Learning with Differential Privacy Huanyu Zhang Ilya Mironov Meisam Hejazinia 11 27 0 01 Mar 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning Da Yu Huishuai Zhang Wei Chen Tie-Yan Liu FedML SILM 99 113 0 25 Feb 2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models Yugeng Liu Rui Wen Xinlei He A. Salem Zhikun Zhang Michael Backes Emiliano De Cristofaro Mario Fritz Yang Zhang AAML 41 128 0 04 Feb 2021
Characterizing signal propagation to close the performance gap in unnormalized ResNets Andrew Brock Soham De Samuel L. Smith 95 123 0 21 Jan 2021
Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning Milad Nasr Shuang Song Abhradeep Thakurta Nicolas Papernot Nicholas Carlini MIACV FedML 105 219 0 11 Jan 2021
Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling Vitaly Feldman Audra McMillan Kunal Talwar FedML 41 159 0 23 Dec 2020
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 398 1,868 0 14 Dec 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 259 40,217 0 22 Oct 2020
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization P. Subramani Nicholas Vadivelu Gautam Kamath 31 83 0 18 Oct 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 157 1,314 0 03 Oct 2020
Label-Only Membership Inference Attacks Christopher A. Choquette-Choo Florian Tramèr Nicholas Carlini Nicolas Papernot MIACV MIALM 54 500 0 28 Jul 2020
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification Yingxue Zhou Zhiwei Steven Wu A. Banerjee 48 108 0 07 Jul 2020
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses Raef Bassily Vitaly Feldman Cristóbal Guzmán Kunal Talwar MLT 41 193 0 12 Jun 2020
Evading Curse of Dimensionality in Unconstrained Private GLMs via Private Gradient Descent Shuang Song Thomas Steinke Om Thakkar Abhradeep Thakurta 43 50 0 11 Jun 2020
Big Transfer (BiT): General Visual Representation Learning Alexander Kolesnikov Lucas Beyer Xiaohua Zhai J. Puigcerver Jessica Yung Sylvain Gelly N. Houlsby MQ 209 1,196 0 24 Dec 2019
RandAugment: Practical automated data augmentation with a reduced search space E. D. Cubuk Barret Zoph Jonathon Shlens Quoc V. Le MQ 179 3,458 0 30 Sep 2019
Rényi Differential Privacy of the Sampled Gaussian Mechanism Ilya Mironov Kunal Talwar Li Zhang 32 280 0 28 Aug 2019
Private Stochastic Convex Optimization with Optimal Rates Raef Bassily Vitaly Feldman Kunal Talwar Abhradeep Thakurta 41 239 0 27 Aug 2019
AdaCliP: Adaptive Clipping for Private SGD Venkatadheeraj Pichapati A. Suresh Felix X. Yu Sashank J. Reddi Sanjiv Kumar 24 123 0 20 Aug 2019
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model Guodong Zhang Lala Li Zachary Nado James Martens Sushant Sachdeva George E. Dahl Christopher J. Shallue Roger C. Grosse 71 150 0 09 Jul 2019
Differentially Private Learning with Adaptive Clipping Galen Andrew Om Thakkar H. B. McMahan Swaroop Ramaswamy FedML 47 335 0 09 May 2019
Large Batch Optimization for Deep Learning: Training BERT in 76 minutes Yang You Jing Li Sashank J. Reddi Jonathan Hseu Sanjiv Kumar Srinadh Bhojanapalli Xiaodan Song J. Demmel Kurt Keutzer Cho-Jui Hsieh ODL 151 991 0 01 Apr 2019
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy T. Tony Cai Yichen Wang Linjun Zhang 51 165 0 12 Feb 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 167 423 0 29 Nov 2018
Subsampled Rényi Differential Privacy and Analytical Moments Accountant Yu Wang Borja Balle S. Kasiviswanathan 54 397 0 31 Jul 2018
Revisiting differentially private linear regression: optimal and adaptive prediction & estimation in unbounded domain Yu Wang 26 95 0 07 Mar 2018
Shampoo: Preconditioned Stochastic Tensor Optimization Vineet Gupta Tomer Koren Y. Singer ODL 43 214 0 26 Feb 2018