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Adversarial Samples

Technology
1 of 18
Adversarial Samples Zhedong Zheng University of Technology Sydney 2018-3-31
What?
Define
Formulation
Why? Other Network
Why? Linear Classifier
Why?
Why?
Why? CVPR 2016
How? • 1. The Basic Iteration Method • 2. Fast Method (and Fig) • 3. Least-likely Method
The Basic Iteration Method
Fast Method (and Fig)
Least-likely Method
Compare
Compare
Application
Reference • Adversarial examples in the physical world (ICLR2017 Workshop) • Ian Speech on CS231n • DeepFool: a simple and accurate method to fool deep neural networks (CVPR2016) The idea in this work is close to the orginal idea. Loop until the predicted label change. • Learning with a strong adversary (rejected by ICLR2016?) Apply the spirit of GAN to optimization. • Explaining and Harnessing Adversarial Examples (ICLR2015) Fast Gradient Sign Method • Exploring the space of adversarial images IJCNN

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