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Attacking machine learning with adversarial examples
Adversarial examples are inputs to machine learning models that an attacker has intentionally designed to cause the model to make a mistake; they’re like optical illusions for machines. In this post we’ll show how adversarial examples work across different mediums, and will discuss why securing systems against them…
- Points
- 308
- HN comments
- 82
- Submissions
- 1
- Cited by
- 7 commenters
AI & Machine LearningSecurity & Privacy2017
On Hacker News
| Submitted | Title on HN | Points | Comments |
|---|---|---|---|
| Feb 16, 2017 | Attacking machine learning with adversarial examples by dwaxe | 308 | 82 |
Cited in comments
Linked from 7 Hacker News comments by 7 different people, from Feb 2017 to Nov 2021.
Most recent:
- tech_timc · Nov 13, 2021
- the8472 · Aug 18, 2021
- jll29 · Aug 6, 2021
- throwaway-87398 · May 5, 2020
- dijksterhuis · Apr 2, 2019
- soravux · Mar 6, 2017
