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Introduction
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Classroom Contents
The Current State of Adversarial Machine Learning
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- 1 Introduction
- 2 Who am I
- 3 I know were okay
- 4 Adding noise
- 5 What happens
- 6 Image classifiers
- 7 Terminology
- 8 Outline
- 9 Timeline
- 10 Types of Attacks
- 11 Blind Spots
- 12 Bugs
- 13 Examples
- 14 Alchemy
- 15 Generating adversarial examples
- 16 What can we do
- 17 Training life cycle
- 18 Visual understanding
- 19 Reservoir sampling
- 20 Notable research
- 21 Demo
- 22 TF Classification
- 23 References
- 24 Resources
- 25 Takeaway
- 26 Interview
