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We demonstrate self-supervised pretraining (SSP) is a scalable solution to deep learning with differential privacy (DP) regardless of the size of available public datasets in image classification.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Medical image and data sharing: are we there yet?
Adam E Flanders · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky et al · 2009
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Differentially private empirical risk minimization
Kamalika Chaudhuri, Claire Monteleoni, and Anand D Sarwate · 2011
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Bayesian learning via stochastic gradient langevin dynamics
Max Welling and Yee W Teh · 2011
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Deep roto-translation scattering for object classification
Edouard Oyallon and Stephane Mallat · 2015
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Privacy for free: Posterior sampling and stochastic gradient monte carlo
Yu-Xiang Wang, Stephen Fienberg, and Alex Smola · 2015
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Deep learning with differential privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Direct feedback alignment provides learning in deep neural networks
Arild Nø kland · 2016
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Convolutional neural networks for medical image analysis: Full training or fine tuning?
Nima Tajbakhsh, Jae Y Shin, Suryakanth R Gurudu, R Todd Hurst, Christopher B Kendall, Michael B Gotway, and Jianming Liang · 2016
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Daan Wierstra, et al · 2016
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Rényi differential privacy
Ilya Mironov · 2017
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Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov · 2017
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What makes instance discrimination good for transfer learning?
Nanxuan Zhao, Zhirong Wu, Rynson W. H. Lau, and Stephen Lin · 2017
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Deep learning for detecting cyberbullying across multiple social media platforms
Sweta Agrawal and Amit Awekar · 2018
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Skin lesion analysis toward melanoma detection: A challenge at the 2017 international symposium on biomedical imaging (isbi), hosted by the international skin imaging collaboration (isic)
Noel CF Codella, David Gutman, M Emre Celebi, Brian Helba, Michael A Marchetti, Stephen W Dusza, Aadi Kalloo, Konstantinos Liopyris, Nabin Mishra, Harald Kittler, et al · 2018
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Big self-supervised models are strong semi-supervised learners
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey E Hinton · 2020
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Differentially private deep learning with direct feedback alignment
Jaewoo Lee and Daniel Kifer · 2020
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A critical analysis of self-supervision, or what we can learn from a single image
Asano YM., Rupprecht C., and Vedaldi A · 2020
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Pass: An imagenet replacement for self-supervised pretraining without humans
Yuki M. Asano, Christian Rupprecht, Andrew Zisserman, and Andrea Vedaldi · 2021
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Differentially private bayesian neural networks on accuracy, privacy and reliability
Zhiqi Bu, Qiyiwen Zhang, Kan Chen, and Qi Long · 2021
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Deep learning with long short-term memory networks for financial market predictions
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Scattering networks for hybrid representation learning
Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew Blaschko, and Eugene Belilovsky · 2018
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Scalable private learning with PATE
Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Ulfar Erlingsson · 2018
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The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions
Philipp Tschandl, Cliff Rosendahl, and Harald Kittler · 2018
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Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification
Patrick Helber, Benjamin Bischke, Andreas Dengel, and Damian Borth · 2019
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Harmonic networks for image classification
Matej Ulicny, Vladimir A Krylov, and Rozenn Dahyot · 2019
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Deep learning with gaussian differential privacy
Zhiqi Bu, Jinshuo Dong, Qi Long, and Weijie Su · 2020
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Extracting training data from large language models
Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, and Colin Raffel · 2021
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Scalable differential privacy with sparse network finetuning
Zelun Luo, Daniel J. Wu, Ehsan Adeli, and Li Fei-Fei · 2021
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The role of adaptive optimizers for honest private hyperparameter selection
Shubhankar Mohapatra, Sajin Sasy, Xi He, Gautam Kamath, and Om Thakkar · 2021
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Photonic differential privacy with direct feedback alignment
Ruben Ohana, Hamlet Medina, Julien Launay, Alessandro Cappelli, Iacopo Poli, Liva Ralaivola, and Alain Rakotomamonjy · 2021
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Differentially private learning needs better features (or much more data)
Florian Tramer and Dan Boneh · 2021
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Opacus: User-friendly differential privacy library in pytorch
Ashkan Yousefpour, Igor Shilov, Alexandre Sablayrolles, Davide Testuggine, Karthik Prasad, Mani Malek, John Nguyen, Sayan Ghosh, Akash Bharadwaj, Jessica Zhao, Graham Cormode, and Ilya Mironov · 2021
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Toward training at imagenet scale with differential privacy
Alexey Kurakin, Steve Chien, Shuang Song, Roxana Geambasu, Andreas Terzis, and Abhradeep Thakurta · 2022
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