Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image
Encoders

Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders

19 January 2022

Michael Backes

Papers citing "Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders"

7 / 57 papers shown

Title
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 512 5,878 0 08 Jul 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 60 3,660 0 08 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.7K 192,638 0 10 Dec 2015
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 74 3,947 0 24 Nov 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 294 19,523 0 09 Mar 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.3K 149,474 0 22 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 215 18,922 0 20 Dec 2014