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Differentially Private Learning Needs Better Features (or Much More Data)

Nov 26, 2020
Florian Tramèr, Dan Boneh

* 29 pages. Code available at https://github.com/ftramer/Handcrafted-DP 

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How Relevant is the Turing Test in the Age of Sophisbots?

Aug 30, 2019
Dan Boneh, Andrew J. Grotto, Patrick McDaniel, Nicolas Papernot


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Adversarial Training and Robustness for Multiple Perturbations

Apr 30, 2019
Florian Tramèr, Dan Boneh

* 22 pages 

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Ad-versarial: Defeating Perceptual Ad-Blocking

Nov 08, 2018
Florian Tramèr, Pascal Dupré, Gili Rusak, Giancarlo Pellegrino, Dan Boneh

* 19 pages, 12 figures 

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Ensemble Adversarial Training: Attacks and Defenses

Jul 22, 2018
Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, Patrick McDaniel

* 20 pages, 5 figures, International Conference on Learning Representations (ICLR) 2018 

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Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware

Jun 08, 2018
Florian Tramer, Dan Boneh


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The Space of Transferable Adversarial Examples

May 23, 2017
Florian Tramèr, Nicolas Papernot, Ian Goodfellow, Dan Boneh, Patrick McDaniel

* 15 pages, 7 figures 

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