Security and Privacy of Machine Learning

Wrap Up

6 May, 2018 · by David Evans

Thanks for a great semester!

Here’s the topics we covered:

Class 1: Intro to Adversarial Machine Learning
Class 2: Privacy in Machine Learning
Class 3: Adversarial Machine Learning
Class 4: Differential Privacy In Action
Class 5: Adversarial Machine Learning in Non-Image Domains
Class 6: Measuring Robustness of ML Models
Class 7: Biases in ML, Discriminatory Advertising
Class 8: Testing of Deep Networks
Class 9: Adversarial Malware Detection
Class 10: Formal Verification Methods
Class 11: Poisoning